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  {
   "cells": [
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Inspired by Jason at [Almost Looks Like Work](http://jasmcole.com/2014/10/19/going-viral/) I wanted to take on some modeling of disease spread. Note that this model has no claim what so ever on reflecting reality and is not to be mistaken for the horrible epidemic in West Africa. On the contrary, it's more to be viewed as some sort of fictional zombie outbreak. That said, let's get down to it!"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "$$ \n",
      "\\begin{align}\n",
      "u(t) & = \\begin{pmatrix} S \\\\ I \\\\ R \\end{pmatrix} & f(u)   = u'(t) = \\begin{pmatrix} S' \\\\ I' \\\\ R' \\end{pmatrix}  = \\begin{pmatrix}\n",
      "  -\\beta I S  \\\\\n",
      "  \\beta I S - \\gamma I  \\\\\n",
      " \\gamma I\n",
      "\\end{pmatrix} \n",
      "\\end{align}\n",
      "$$"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "This is what's called a [SIR model]() where the letters S, I and R reflects different states an individual can have in a zombie outbreak:\n",
      "\n",
      "  * $S$ for susceptible. Number of healthy individuals that potentially could turn.\n",
      "  * $U$ for infected. Number of *walkers*.\n",
      "  * $R$ for removed. Number of individuals that's out of the game by separation of head from body (if I know my zombie movies correctly), or that survived. But there's no cure of \"zombie:ism\", so let's not fool ourselves (it might be the case thou if the SIR model is used for flu epidemics).\n",
      "  \n",
      "We also have $\\beta$ and $\\gamma$:\n",
      "\n",
      "  * $\\beta$ is how transmittable the disease is. One bite is all it takes!\n",
      "  * $\\gamma$ is how fast you go from zombie to dead. Has to be some sort of average of how fast our zombie hunters is working... Well it's not a perfect model. Bare with me.\n",
      "  \n",
      "So $S' = -\\beta I S$ tells us how fast people are turning into zombies. $S'$ being the time derivative.\n",
      "\n",
      "$I' = \\beta I S - \\gamma I$ tells us how the infected increases and how fast the zombie workers are putting zombies in the *removed* state (pun intended).\n",
      "\n",
      "$R' = \\gamma I$ just picks up the $\\gamma I$ term that was negative in the previous equation."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The above model does not take into account that there must be spatial distribution of S/I/R. So let's fix that!\n",
      "\n",
      "One approach is to divide Sweden and the Nordic countries into a grid where every cell can infect the nearby. This can be described as follows:"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "$$\n",
      "\\begin{align}\n",
      " f(u)   = u'(t)  = \\begin{pmatrix} S' \\\\ I' \\\\ R' \\end{pmatrix} = \\begin{pmatrix}\n",
      "  -\\beta \\left(S_{i,j}I_{i,j} + S_{i-1,j}I_{i-1,j} + S_{i+1,j}I_{i+1,j} + S_{i,j-1}I_{i,j-1} + S_{i,j+1}I_{i,j+1}\\right)  \\\\\n",
      "  \\beta \\left(S_{i,j}I_{i,j} + S_{i-1,j}I_{i-1,j} + S_{i+1,j}I_{i+1,j} + S_{i,j-1}I_{i,j-1} + S_{i,j+1}I_{i,j+1}\\right) - \\gamma I_{i,j}  \\\\\n",
      " \\gamma I_{i,j}\n",
      "\\end{pmatrix} \n",
      "\\end{align}\n",
      "$$"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Where for example $$S_{ij}$$ being one cell and $$S_{i-1j}$$, $$S_{i+1j}$$, $$S_{ij-1}$$ and $$S_{ij+1}$$ being the surrounding cells (let's not make our brains tired with the diagonal cells, we need our brain for not getting our brain eaten)."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Initializing some stuff."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import numpy as np\n",
      "import math\n",
      "import matplotlib.pyplot as plt    \n",
      "%matplotlib inline\n",
      "from matplotlib import rcParams\n",
      "import matplotlib.image as mpimg\n",
      "rcParams['font.family'] = 'serif'\n",
      "rcParams['font.size'] = 16\n",
      "rcParams['figure.figsize'] = 12, 8\n",
      "from PIL import Image"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 14
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Some appropriate beta and gamma making sure to wipe out most of the country."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "beta = 0.010\n",
      "gamma = 1"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 4
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Remember the definition of a derivative? With some rearranging it can actually be used to approximate  the next step of the function when the derivative is known and $\\Delta t$ is assumed to be small. And we have already stated $u'(t)$."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "$$ \n",
      "u'(t) = \\mathop {\\lim }\\limits_{\\Delta t \\to 0} \\frac{ {u\\left( {t + \\Delta t } \\right) - u\\left( t \\right)}}{\\Delta t}  $$ \n",
      "\n",
      "$$ \n",
      "u' \\Delta t + u\\left( t \\right)= {u\\left( {t + \\Delta t } \\right)}  $$ \n",
      "\n",
      "Remember from before\n",
      "\n",
      "$$  f(u)   = u'(t)$$\n",
      "\n",
      "And let's call $u\\left( {t + \\Delta t } \\right)$ which is the function $u$ in the next time step for $u_{n+1}$, and $u(t) = u_n$ which is the current time step.\n",
      "\n",
      "$$  u_{n+1} = f(u)\\Delta t + u_n  $$\n",
      "\n",
      "This is called [the Euler method](http://en.wikipedia.org/wiki/Euler_method). Let's write it in code:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def euler_step(u, f, dt):\n",
      "    return u + dt * f(u)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 5
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "We also need $f(u)$ in code. This uses some nifty array operations by the goodness of numpy. I just might get back to that in another blog post, because they're great and might need some more explaining. But for now this will do."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def f(u):\n",
      "    S = u[0]\n",
      "    I = u[1]\n",
      "    R = u[2]\n",
      "    \n",
      "    new = np.array([-beta*(S[1:-1, 1:-1]*I[1:-1, 1:-1] + \\\n",
      "                            S[0:-2, 1:-1]*I[0:-2, 1:-1] + \\\n",
      "                            S[2:, 1:-1]*I[2:, 1:-1] + \\\n",
      "                            S[1:-1, 0:-2]*I[1:-1, 0:-2] + \\\n",
      "                            S[1:-1, 2:]*I[1:-1, 2:]),\n",
      "                     beta*(S[1:-1, 1:-1]*I[1:-1, 1:-1] + \\\n",
      "                            S[0:-2, 1:-1]*I[0:-2, 1:-1] + \\\n",
      "                            S[2:, 1:-1]*I[2:, 1:-1] + \\\n",
      "                            S[1:-1, 0:-2]*I[1:-1, 0:-2] + \\\n",
      "                            S[1:-1, 2:]*I[1:-1, 2:]) - gamma*I[1:-1, 1:-1],\n",
      "                     gamma*I[1:-1, 1:-1]\n",
      "                    ])\n",
      "    \n",
      "    padding = np.zeros_like(u)\n",
      "    padding[:,1:-1,1:-1] = new\n",
      "    padding[0][padding[0] < 0] = 0\n",
      "    padding[0][padding[0] > 255] = 255\n",
      "    padding[1][padding[1] < 0] = 0\n",
      "    padding[1][padding[1] > 255] = 255\n",
      "    padding[2][padding[2] < 0] = 0\n",
      "    padding[2][padding[2] > 255] = 255\n",
      "    \n",
      "    return padding"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 6
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Here I import an map with the population density of the Nordic countries and downsample it to make the solving time resonably fast."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from PIL import Image\n",
      "img = Image.open('popdens2.png')\n",
      "img = img.resize((img.size[0]/2,img.size[1]/2)) \n",
      "img = 255 - np.asarray(img)\n",
      "imgplot = plt.imshow(img)\n",
      "imgplot.set_interpolation('nearest')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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a29sJWFDkTPneddddJceJ8de6rpOu6+T3+6mpqYnq6+vJ7/fTgQMH+Gs/i5ph\nMdLZbJaSyWTZvojKU/SXOyX/2J2/nH51JxeGYRglfQkGgzzu32lSK3fPV+PZPvDAA7ax/NXKco5p\nLUUqdSnXjfzJn/yJI5ufndIRFyUVRaGmpia+EOjz+ei2224jAJRKpUxKJZ/PUyaTKWnfbT+Z0r4a\n2Z120tLSYrudWeorFf7IJtHFnCsXS98WqdSlXHfCFkNFxWsYBmmaxpV4T08P+Xw+TivARFVV6ujo\ncFQit956KwGghx9+2FXBhkpKzLpYezUUrF2Gq10f3FqyUsHWVtzqTLlQKnHNIhqNYsuWLfzz3Nwc\nUqkUzp07h6amJqiqipmZGRQKBfj9fjQ0NGBmZoZ/+X0+H48X1zQNmUzGxKio6zoURcGjjz6KUCiE\nhoYG/M3f/I2pYINTlmS5upsA7IwX/ne5MD4+7qoPYoELp/vRNA2BQGBZ++cEVsJPYpGotSUuLXUp\ni5H29nYegsgsZ6/XSz6fj3Rdpw0bNnBr2Q2fCYtxB0Af/OAHKZFIUDAY5NZpOBymRCJRtY93Nfpz\nrYuhlUi/2P9OhUbYuoaUqyvS/SJlzcjAwAABCz5tpmRYjPrQ0BCPSBFZERk1QD6fdySECgaDfEEU\nWFDsf/zHf8zj3tPpNCmK4uibBq59l0SlaB1rfD/7v1wcuZjAtRxyrY/xcolU6lKuaamvr6f6+noK\nBAIUCoV4xqeiKI50uvv376/qGkxZhEIhCofDvN3FMCXWeryWKlalzqxyxkrpdI+VeG4WI27ehq7H\nQtRudaZyRXGuWlz5MklcR+jo6EBLSwsAwOfz4X/+538wMzODyclJtLe34yc/+QkA4ODBg3jyyScx\nPz/vuvAxK0PHkEgkMDMzg4mJCYTDYYyPj0P8TTDekmQyaVsSj/mgV/vvqBIYv8vc3BxUVYWiKJxF\nshJvSyAQ4MWkw+EwxsbGAJSOtVu4OU/TtCWzXF5rICJXNJdyoVRiVUFRFPzsZz9DPB5HPB7HN77x\nDfj9fqTTaczMzODUqVO48cYb0dbWhsceewyzs7NVKdS6ujp4PB54PB4YhoHR0VFOwDU2NlbSFhGh\no6MD586dw+bNm0vaE94oq77P5UY0GuU0utbSfJUwNzdnWgAuFAq8DVZn1QmTk5Oc2Izdl8fjQTgc\nrqoPDG7Ou94UelWotXtFul+kMGGv+n/wB39A8Xic4vF4iT98Ma4O5mv3+XwUjUZLyLP8fj8pimIi\nrXLb9mpma1yAAAAgAElEQVRzvzAXkjVksxphoZC9vb0UCAR4BahyxSoY5451XJfrvhY7xpXCOq8l\ncaszpaUusSqQSqXQ1taGz3zmMzh58iQvCv2Od7zDdFw1VnFraysMw0BDQwMAYP/+/RgbG0OxWOSv\n9x6PB1NTUyAizM/PQ9f1Bb+kpb5nubqiq8n1wuqsTk9PV3VeJpNBJpMB8HYo5E9/+lNMTk5ibm4O\nXq8XiqJg3bp1pvMYxe5jjz2G8fFxk9tkOYtbLHaMrWGdV+MNadWh1pa4tNSlrFu3jvL5PAHgf1nJ\nuaW2fdNNN/FImdbW1hKLLxQKlaXOFZNzrIuJq81KX07Rdb0kwiUWizmGaB46dMh0vF19VrfhnfF4\nvGJ9VzfC3hTWyqKqa51Za6Utlfr1LaqqUmNjIzU1NS17293d3fx/5trJ5XI0ODhIg4ODpu1OfbPL\nDF2JFHu/319T+llFUcgwjBJahEqZsiw8kvV9x44dtm1Xuj5TxGIN2OtdpPtFYtWDuTZ27NhhG1my\nFKxbtw4XL15EMplEMpnk7pORkRG89NJLeOmll6CqKmZnZ3lfrH0rFouOmaFXy+XCsjaJCNFoFLqu\nX5XriPerqioaGxvR2NjItxERZmZmMDw8bDqn3AKlYRggIiSTST4+//3f/11ynOjKyuVy3O0jIpVK\nQdd1Uw1Yhmw2i1QqVfb+Nm3aVNZltqZRhcVcD+AxAEVpqUtZDolEIiZrejnaK1eVJ5/Pc1cME03T\nKBAIlNQmdeMquFrWOrNyGYXwUhY97cQuDpzdC0scWkwm7C/90i9ROBymhoYG2z7bjZXYF8MwuMut\n3FuKuKgtCnvbW84F2tUky+p+AXAIwOsAjgIolDkuBOB/XznuJwD+PwA9Nsd5AHwawE8BvAzgvwDs\nkkr9+pPlTF7ZtWsXNTQ00MaNGwlY8OuK/OdiBSBRwYg0uYu5bjXKXawoZHeOoig0ODhITz31FCmK\nQtu3b6e9e/fS5s2bK/ah3P62tjYCzMpSXEvwer0VFbqqqhWzRVk/6+vrbSNPmLK3a4fRF7DnByyQ\ns+VyuaomtrUU8SLKciv1/wKQB/AVlLHUAfw7gP8E4Lvy+Q8ADAPIWY77AhYUf/LK50cATADol0r9\n+hEnLpHFCFPY0WiUbrnlFttiD4wDxuPxkMfjoZ07d5Ycs9yWN2uPKVWrqKrKwwbt9lXqUzX+6Wp4\na5wUu6IorhYexWPEEFKR917X9ZIasIZh8IknkUhQT09P1X1fbM3Y1S7LrdRZ5ulX4KDUAbwDQBHA\nXotFPgLgfwvbOgEUALzbcv6PAfybVOpSqhX2Kh4KhSidTpe11JwUkpPVvFL3oCgK9fb2ksfjceSG\nLyeV3CXsXqxuC6exKqe8rS4sUTKZjGP1JJ/PZ7sgbl2s/va3v03hcHjRz0QkZ6sky+3aupqyrEpd\nULBfgbNS/wKAaQC6Zfv/C+C08Pm3sKD8WyzH/QWAWQABqdSlVCN21pzP57NlG6ykKK524YpKwkL5\nxNJ4lc4Rfcz/63/9r6o40p2iWRSltLA28LbbJBKJLEtVIiY33XQT7/Phw4f59mg0WtX4swmxu7ub\nQqEQNTc3UyKRWNHv49WSWij1ZwG8brP9z7GgxFNXPv8dgDlcsf6F437jynGDUqlLWYy8613vop6e\nHurv7y9RBHaWp90xTm3XOh7den3DMErC/dgxTPE2NjY6TmaVXChsvOrr6wkAJZNJboGHw2FucYu+\ncUVRaPPmzVWPFXOLieft2LGDvF4v7du3z/XkwSZE65tOuXuVlnp5pf4zAC/abP9DLCjrziufvw3g\nks1x/9eV4w5IpS6lGtm3bx81NDSQruu2CoL9bxgG50h3a8WLx6xGbnQ3wvqtqir3V1da8BTv1W5c\nxAVua6SKW+rdRCJBsVjM0ZK2i2IJBAJcSVvfMlRVdUxaUhTF5JZhFbFq/WyqEbd6+joN5JSoFT7y\nkY8se5tPPfUUTp48ie3bt+PixYsAACLizIOqqsLv9yMSiWBiYoJ/+athWCRaqBC0GtLMw+FwRZIt\nAKZKRclkEsViETMzMwCArq6usucqigKv1wsAZeO9PR5PxTEJBAK2VZOKxSIuXryICxculFxH0zRb\nmgFGW5DP501jEAqFUCwWMTExYdsHIsL58+cBAIcOHeIVsdYillOpnwdgR68WufJ3RDguqJR+E6zH\nSUhISEhUi2VeKJ1B6ULpNwCcEj5/AgtulmabhdIZyIVSKcsgHo+Hu1kYCyNQPtqjWl9wLd0xrIyf\nlR8nkUhwt4TVPaEoCndPNDc3V7wG86GL7hWRwdHuHJ/P5+hOsUalNDY28jG0umxisRiFw2HSdd3x\nuSxl/Ldt23bNJSldTZ+6bfIR3g5p3CNs8wIYBfAXwrYOLIQ0/orl/B8D+IZNuzUfTCnXpliVWjAY\ntFXqS1kEXe7oGE3TSFEU8vl8ZZWW3STFjm9ubub+4s2bN5f4mW+77baScbG2v27dOv6/x+OhWCxG\nXV1dlEwmKypTsb14PE65XI6HQbJIJcBcK9VuDJnStfq+2eTwyCOPLGmsrzWirxVfKL2ynyUf+a98\n/n0AZwHUW477PzAnH70HC8lHG6VSXzuykpEF5cIPNU2jPXv2lJBTAW8TUC1VMa+kghCVarmi2nbx\n4m4WMRl1griNWetMwZa733Q6zY+3O07Xddu+WZ+PNX5dfEYswiWfz3NmT7v7Zm9q7HM2m+VvEpWy\ndFebLKtSB/CXAN4AMIYFK/sNLNAGeCzHBbFAE3AMwCtYoAnotmlPxwJNwFFImoA1KdUkgCxVtm/f\nbrs9EolQe3t72df35YxFX+mwR4/HYztRbdq0ibxer4kt0SqixVxJ0duFgxqGYTuhWLl8tmzZYvq8\nfv16x+voum4yBJwiWW644QbulmG1bK3HDA0NUTabLXlrWLduHSmKUjIRXAtyVSz1WkitB1LK6ham\nWILBIK9qxPblcjnbDMarmVS0kslK1YTksTWGxd4TsGAds0liy5YtjpNBIBCgDRs22E44wILyZhNq\nuWs60UgkEgk+znV1dSXx+mwCYuGPuq5TJBLh1j3rl91ksJrFrc6UIY0Sqx6hUMhx3+zsLAKBACYm\nJkw1RhVFwezsLOLxOACUVOy5WhCMkWUPf9R13UTFy0IOrUgkEiXb5ubmEAwG+WcWDjgwMMDDF71e\nLzweD3p6etDV1YXW1lY0NTXx+xkbG0OhUIDf78fLL7/M28jn86Zrzc7O4sc//jFisZht/+bn5+Hx\neHi7VtTV1SEajTrSMY+OjgJYGGtG38yg6zqi0Sja2tp4+OP8/Dymp6cxNjaGbDYLv98PADh79qxt\n+9c8am2JS0tdSjmpVAHHup9Zf+l0mvx+P6XTaXrooYdKjllpXpflaEcku1qMsEVYJ6oEtp1ZusFg\nsISDxePx0O7du/k20V2iqmpJnVK7dRXrPVgt5mreQIaGhmhoaMh0nt2bGPPPZ7NZ+tCHPrRiz345\nRbpfpKxJEX+onZ2dBJRGuQwMDHDFdPvtt5cokVpwumiaVvVi6mL6x+h6Kx0XjUZt3RuappUoVeZm\nYf2xMivmcjnbqCJN02wnoXKEayzyx26f9brAQonC1tbWku+ASLnMqHvFyWbTpk38ej09PTWngXAj\nUqlLWdNy7733lkRRMCuxv7+fgAWrbNu2bY5t1Eq5uz22Uuig3X67Cczp+FtvvdWxbV3X+VuQSBgG\n2EfVlPORM793pfsJBAKODI9MnCZGu3q2iqLQvffeS6qqViT1WktKnVHqrlpcGWwJCY5vfvOb+OpX\nvwrDMHD69Gn88Ic/xOjoKAqFArZv34433ngDyWQS/f39+Pu//3tomsar3Fu/79VQBSwXFEWp6nqh\nUAjj4+O44447AAA/+MEPcPr0aZ6iz0ryMei6jvn5eeRyOZw6dQper7fkGDd9HBoawnPPPQcA8Pl8\nmJ6ehq7rICIYhoHJycmq2gwGg4jH4zh58qTj/bPrVIKmadA0jY/Jv/7rv/JnLCKfz+PEiROO7bCx\nBRYoD+bm5lzcSW1ARO4WaWptiUtLXcpiZd++fbR3714CFkIoWRhlIBCge+65h3bv3u2qoPVKW2mL\nuV5DQwMxAKUuJ4/H4/gWwK4nRomUy6YU1ylExkOx7J+1PafrWu/1jjvuIK/XS6lUypb2t9Iaiigd\nHR38/w0bNpTsZ333+XxlcybcEpDVWqT7RcqaFEVRqL29nYLBIAUCAYpGo5TJZGjbtm0UCARKlFUq\nlSJFUcq+1tfy1bsaJcaEuSAymQxnS2xsbORK0k36fD6fL6voNE2zVbosQ9TtvdndX19fn+M5gUCg\nbEIVE3aPX//61+nrX/86bdq0id7xjncQ8Ha8e7mYeLvxXO0ilbqUa1rEAhFWfmw7/+mOHTtKtjHl\nISrtxsZGUz1OJrVU7E6FKtxKKpUiwzBMqf0A6MCBAyWl7FgEjFheDliw3P1+v2PVJU3TKBQK8VJx\nqqqaLHU2fsxitlOoTFnbPT9xW7m6taxohnWxVVVV0jSN6uvrTVTDdm3YPeutW7euer+6VOpS1pSs\nX7+eotEodXV1EVC6yKkoCu3evZsfH41G6eDBg/yz+INtaWmhlpaWkmss94+6mrJ0Pp9vSfzeLOuT\nKW3rPrbYad1njYBhyrKpqcmUFVxubDRNo/Xr17t6Q1BVlbZs2VLy5uT1eksmJTfXZmGeYl1TsV92\nbxzJZJJaWlr4vUajUYpGo0sKF10JkUpdypqSUChE9fX11NfXR8lkkm8Xf7BMCQWDQdq5c2fJq79b\npVkri60arhyri8LpzYO5o9hnuzGoNC51dXUlY8LGOpvNUn19fYl1HQwG+dsWewtg+9hk5zTOTspd\nlHIuEytnDJts7CZORVEok8mYCqxU+yxWStzqTJlRKnFNoLOzE4VCARcvXsTIyAh0XUc+n8f8/Dz8\nfj8Mw0BdXR1UVcXExAR+9rOflRRMKBQKPAORRb3YZX1eMSZWHDt37nTMnrX28+LFi6ZtLEsyGo2i\ns7MTRISGhgZMTU2hubkZRAS/349CoWDK9FQUpaRYRFtbG/8/EAjgzJkzpjHJ5XI8i/Ts2bM4d+6c\nKTtTURRMTEygWCyiWCxiamqKF7xobGxENptFJBIBEdlmxVozYsPhMO+zz+cDANsoFTYely9fNhXQ\nYFEx09PTKBQKpgxYIsLw8DCCwSDGxsZM29n3xC5Dd1Wj1pa4tNSlVJJcLkfxeNxEQqXrOvX19dGh\nQ4dsOUZ+93d/lwzDKOsSqMTQKLp2VvJ+FxM7z+hx2Were4O1KZa0E/cxq5pZuZqmcf+5OF7i9djb\nga7rtHPnTopGo7Z8Kslk0vR2lU6n6dFHHyVgwX3S1tbGXUMsSUhVVR63Lo5FLBbj/vdq+NDFZCRV\nVW1dY24WaGsp0v0i5ZoVwzBo06ZNPOuPZY46Kbre3t4SJTY0NGS7IAeYF2EXq7ArvZ67mSzcSrnj\nra4GUUKhUMm6A/C2y6pcu1b3htfrJcMwTO2JSj4ej1M8HifDMCgQCHCaBpZJ6/F4aP369bR161bO\n5NjY2EiRSIT7tpPJJLW2tlYcD/G6TPFv3Lix7Ni1tbWRpmkUjUZp165dfH9TU5PJJTM4OMgzV90k\nQ62kSKUu5ZqTRCJB27dvp02bNlEoFCrhEbGTQCDALXXx2K6uLvL5fLbshIvNJHU6/movsFXqZyWf\nuDWbkilnYGFy0nWdixhVIlaPYttUVaWGhgau9K3WMrPerYusTvfwwAMPmP7aidP3oFwMvXht6xuZ\nXbQR2x+NRikSiZCmaSVrAbUWtzpT+tQlVg1GR0fx3HPPobu7G5FIBJFIxDZLkEHXdcTjcYyOjkJV\nVdOxp06dwvT0NObm5phxAMDsmxa3u4HT8ayYczkshbGRaMH3bGVpVBQFPT09Jj+8pmklhaJHR0dN\nfuGZmRl+L9PT05ifn+fi8/k4ayMbOyLi1ygWixgZGcHc3Byi0WhJcejZ2VlomsaLPLP+O43d+vXr\nMT4+jpdffhkPPfQQVFVFY2Oj6Zjx8XHuSxcxNjYGVVWhqirS6bTtNZhfnIigaRoaGxsxPz9vOkZV\nVd5Hj8cDTdPg8Xj4WkAkslA+ORQKrYrC4xVRa0tcWupSANDGjRt5uCIjWGKWVSaTcbT0nF6PWQy1\nXbRDLe+TuW2qiU239rnaDEjxfOv6g8fjsXV5xGIx7tcW+xqLxbjv2ckCr6ai0I4dO+iuu+6i3/u9\n36NQKESxWKyEuIvdr13Ei1ORDFFY2GZbWxt3D7F9on+dvaWwtxZGFsZIv2r5vQHcW+qS+0ViVSCb\nzaKrqwuXL1/GCy+8YNrX19eHl19+mVtdzCJvb2/Ha6+9xo8TOVXY/4ZhYGZmhltjAKq20K0ox91S\nDZcM42hxA+ubiHUs3EBRFBiGUcKtomkaj0KxWt6iFcsQCAQ4hwtDMBhEU1MTXnvtNc6X7sSjwvhW\ntmzZAr/fj2eeeca0PxAIwO/34+LFi6ivrwewELkUj8cxMTGBeDyOM2fOYM+ePfjHf/xHAEAkEsHl\ny5fLXi8YDCIajeLUqVN8n9hPZvV3dHSgUCjg2LFj/LhUKsX55ImoJGJoJUAuuV+kUpeoOVpaWgAA\nsVgM3d3deP311/Hzn/8cAHD69Ollu061RFrL2ZZVKdu1F41GMT09jenpadsJyg7RaBSXLl2qqu/x\neBwXLlww9YsV0BDDQPv7+/Hiiy/a9j+dTnMSNYZEIsELWFTCwMAAzp8/z5+z0z3aEXwlk0lcuHAB\nxWKRh1+ePHnSlgiMKWo2ebL2AoEApqamTNdsb29HKpXCK6+8gqamJhw9ehTAQjhtQ0MDnnrqKaiq\nikKhwCeRlVTubpW69KlLSEhIrCFIpS5RcyiKgnXr1sHr9eKVV17B3NwcJiYmMDExgUAg4HjOYq6z\nXHBafLWDWEbODqlUaiFqQVW5tck+W69lxaVLl0yJNuWgKAp0XceFCxfQ0tJict8wKlsRzEoHFtwU\n8XgcHo8Huq7j3LlzfGGRJX+xBChgwZK3LtiKi7yPPPKIyUoHFt7U+vr6TOPJ3loYDMNAIBDgC5/H\njx/H8ePHTVa6qqrQdR3JZBLFYhE9PT1oamqC1+vlC66Tk5MIh8O8TQA4c+YMXnzxRUxPT3MXS6FQ\nwCuvvILHH3+cLyaHw2FcunRp2d76lh21XgiVC6XXr7ACxOxzPp83JanYiRiixj67WfxciQVSRVFs\nKwe5uT5bpPvWt77FU+yt51qTeMRxrNQ36yJjJBIx0dWKC44shNDKC6NcYchknw3DMHHoqKpK27Zt\nK9sftlAstiOODYu7ty62stwCFp5ZKX5cXPRk24LBIA0NDZFhGJTNZk2hneJCKKOX2L9/P+3fv58X\n3GaL72x/Ndw+yyGudWatlbZU6tensB+Eqqp02223UTKZLBvVUU1cuV1cuhuyKafzFyNLTT6yi492\n4gUvV3XIKtYJR9d18vv9praZ0mITlHjN22+/nTZu3Ej9/f0mhR6NRsnj8ZSlEmaK2Ov12kbIWOP9\nQ6GQI0mZ2GYgEDDFxTvxwrCJxDphsjFJJpMUi8Worq6OnnzyScrn85TP50nTNGpsbDT1oRJ/zdUQ\nqdSlrDppa2vj/zPSJjsFLFpXS/3RLCbJaDmlmmu7LRohjmOlcD5xDJz6Iiq5uro6rvyclKO1Bqo4\nGZcrnMF42LPZLOXzeQIWskrr6+spl8uV8LSXI+2qNiTUSgFQaSJk3Ozs2NVAIeBWZ8roF4kVR11d\nHc6cOXPV2l/OKJelYjlCHFnEBvMBK4qCmZkZFAqFiiGRVn+/tR9srN71rncBWCDD+va3vw2/34+5\nuTnevqIoaGlpwcmTJ9HT02PytwMLPnkxEoSFQkajUd6Hixcv8uv39PTglVdeKTsWLGqlUtSQ3X2J\n98b+F9coxIgYwzBQKBSQTCaRSCRw4sQJToQGAG+99RZvKxgMgogwOzuL+fl5xGIxXLx40bF/ywmS\n5eyk1Ersqr5bxev10uHDh6m9vd3k22UWlMjP4kZaWlpKLK9q3BKVZLl4XMqJWx+tlevcSVgyl51/\n3vo/c7Xs3LnT5F+2Wx9obm62fd5uxyKbzdLtt99OwAJPfnNzs6PlHQwGqbu7u6RwtZ3lrCgK97nb\nrT0wLiDGRZNOpymdTpNhGKY3nt7eXhO1QjAYJJ/PR4FAwOQ2Yn1eapETtyLdL1KuCbnllluorq6O\n+1vtFDP7X9M026rwzP/MyKPs2qlGnJSgVZZS1MLNtSuJ9friuU6EY05uGLYIK2achkIh3o71WmIB\nEqfrDAwMmFwz999/P3V0dHBCL7dl69gEVqkmqq7rlE6nHcdw48aN5PV6Sdd1ymazJvcOI/ayc2ep\nqmqq5LTSC6RMpFKXsmqF/ahFwiQn5RkOh7liEFkXxUU3u0XFWvvSFyPlLD7xXtj92h0v+qudxlM8\n126cFEUpWbS2KuByfRVJwRobG3m6PfPFNzc3k8/nq/h8WF/ZtcUJ3e7cdDpd1g/P3gh6e3v5tpaW\nFtNExs4XqXrj8ThFIhEemVOr75VU6lJWhbAfZn9/PwHmH8SBAwdctcEUiGEYvOzYAw88UNEFsdQf\nXyUa2Grar+ZYt9wuXq/XRIPrZJ1bxykQCJRY3iJ1rthfj8fDlTSzgJniY9fzeDzU0dHB28pkMvy5\nNzU10ZEjR+jIkSO83UpvI2y/1+vlFZVExcvqlIpVlerr60vu386F5/QcvF4v9ff3k6Io1NTUZBoT\n8XvM5Gq8pVUSqdSlrGphflmmILq7u8v+UL7xjW8QAPrYxz5GN9xwA4VCIdJ1vWL0x3JY7GJMfLn9\n1e672lLp3nVdt6UN9nq9JouXhRaqqsrDFq1vC+l02lT3k0kgEDDF17ulshX59Fkf/uIv/oLuu+8+\n8vv9JdcB7F1X1rwBu+9YLpcry0vf0NBA6XSacrlcTfnVpVKXsiqlnJL5lV/5FR7ilkqluIX54Q9/\nmD7wgQ/QU089RXv37uUKIhQKkaZpZd0NYjGMauPVV/LeqxWmnEQL1s5St7tmJBIpqdfJxocl5IhW\nOUtCYu2LrpidO3fyxUa27eabb6aBgQECQO9617tM1/b7/bbFS8Tz7YqC+3w+am1t5Uo1lUo5ulo6\nOztL8h7q6upKXEbWtxFFUUxj2NDQ4GrRf6VEKnUpq07Yj2r9+vWk6zodOHDAVNSYxWSLi1IATJVq\nmJRLcgHMyty6vVxkjVOcfDqddowcqUaqSaBiCsbOKmVi56qxbjMMg1vIotKyG4P3vOc9/H+mQJkS\nz2QyFIvFyO/3k67r/DqGYdCWLVuora2N7rrrLgLejkkXrW3x2TmNvzVWvdzzjUQi1NzcbIrG0XWd\nNE2jvr6+knNEA0AcU3FMxOcTjUb5BGRdsF/Ms1+qSKUuZVUJ858zi2nTpk2mHzALo6urq6NMJsOz\n+Vi1+mquVan2KFPq1Spmux/zYn7gbtP62ZuKqqqkaRrPnhTT23VdLwnnVFWVK1x2n0NDQ6RpGgWD\nQVPGKBsLFuZn7R/zaQMLPmaxtKDH4yHDMHiZuLvvvpuAt8MJ6+rqaP/+/SXjZZchWm1yj5XCYP36\n9aSqKrW0tFAulyNd120teVGBa5pGHR0dJoXN7r1cucLVrtQloZfEVQMjTzIMA6qqYteuXRgdHUU8\nHsfs7CzS6TR0XUcoFMKxY8egqirOnDmD5uZmJBIJJBIJnD17FqdPn4amaRWJs8REFMEoKAGrci8m\npFSCx+OxpVll25yIx+zg1C8Rc3NzvHpQsVhEoVDA5OQkJicnTZWWCoUC9uzZYyLjKhaLmJ2d5f97\nvV5cvHgRiqKgqakJLS0t8Hq9KBQKKBaL0DSNjwmwwD+eSCQQDAZx7tw5NDU1we/348KFC/w6RIRM\nJsOToDKZDJ599ll0d3djZGQEgUAAo6Oj6OzsLBkvxkkOAENDQwgGg7h06RJ6e3uRy+WQy+XKjg3j\nVRfx6quvolgsYnx8HCMjI1BVlfOka5qGQCAAXdf5d7K3txcejwfDw8Om5Kb5+Xn4/X5OSGb3/agF\nl3o1kBmlElcNLEOyv78fb7zxBiYnJ00KVfzuWfm6P/ShDwEAvva1r+HcuXMlPyTr+exzJd5yO9gV\nghCRSCRw4cKFkv1erxezs7OIRqO4fPmyK2XN+skyMBeb/Wo9LxqNIhqN4vz585icnLQ9R9d1tLS0\n4NSpU/B6vZiYmIDH40EikeBtsWe2bds2PP/88zh16hQymQyGh4fR3t4Ov9+PqakpHD9+HESESCSC\nyclJzM/P48Ybb0QwGMSbb76Jixcv4vbbb8e//du/cY51VtxCzJwNBAKO/WWTrvXZd3d348yZM5wT\n3gpWko4xN3o8HoTDYd6PZDKJ6elpHD16FH19fchmsxgZGTGV4Ovt7cVPfvITx/EfHBzE97//fcf9\nVwMk+dQlao1CoYDu7m4cO3aMK9pisYhAIIC2tjZkMhkAC4qkWCyarLpXX30Vr776Ks6cOVOSfi7+\nb6WnrVahs3OYlW/3NjA6OmpbI9MwDF5LlYhM1LKVwO6J9VtRFP424vRGItYotU4Ely5dwltvvYVU\nKmXazmh/Ozo6oOs6jh8/jubmZly6dAnz8/PYsmUL6uvrcerUKZw6dQr33HMPhoeH8dhjj6Gvrw93\n3nknGhoasHfvXkxOTnKrd9OmTdi8eTMGBweRyWSwadMmPP300+jp6UEwGMS6devw4IMP4u677+Z9\nOXPmDDRNw/z8PL9HlopvRUNDA4jsKwxNTEzYKnRFURAKhUBEmJ6eRjabhaqqCIVCpuIds7OzmJiY\nQFNTEy5evIhjx47h/Pnz6OnpQTwex5YtW3Ds2DHU1dWhrq4OyWTS9ExUVV1xhV4Vau0zlz71tSmR\nSIQvRjH/57vf/W5qamqiXbt2mRay/H4/7du3z8TceO+999K9995LoVDINl7cKcxwsSnb1sgYu4U8\nsaDti9wAACAASURBVGK9GLfc3t5uG6rH2mA+2HILnk59srvHcqyFALjfm40tYI7k0HWdbrvtNmpo\naKD29nYeqscWRt/5znfy89evX0+08EMkADwefcuWLQQshKJ+9KMfpc7OTsrn85TJZCibzdL9999P\nf/d3f0cbN240kXWJsfX79u3j7ba0tFA6nab169ebFlLtFoIDgYDJ18/GRNd1CofDZRdbRbpnkRjN\nzbOoNO5XW1zrzForbanU16bcdtttpkWy3/qt3+L/79ixw3RsPp+n7u5uzq/BFglTqVTVi6TLFbZY\nDfeMmIUoKkendp36Xe4aLESwkvj9forFYrR3716+7b3vfS8B4BMpu9aHPvQhCoVCtHHjRj7e7Do9\nPT18UXNoaIh+//d/nwzDoGAwaEtB63QP4oQwMDBAuVyOR+OwSYaFM4pRLPl8nk8cdmJV6uLncnQC\ne/fuNYVPivHpbLGWPT+W2MQWlnVdN4Vj2sX4X02RSl1KTeXOO+/k/990000EvB2m5/f7uXJ75zvf\nSZqmmaxYpkwqRRm4oZKtdH65OORqScWq6WMlsXtrEGkVmHi9Xq50WEQKsBAauHnzZnrf+95Hg4OD\nFAwGaXBwkG655RZTGyzqiN2r9U1n69atBNgXpdi4cSPPuHSSeDxOX/jCF+gLX/gCHTlyhD7xiU/Q\n9u3b6XOf+xy34HO5HN1www2m5w9UTvt388z7+vooEAhQQ0MDaZpmmoSCwSA1NzfzN7BwOEyKolAw\nGDTdbywW431i1xHf2lZKpFKXUjNhTHa5XM70im1NL//4xz9OwMIPRFQuYluVCmeInytZjXbCUsIr\nXcPanqhsWLYl6781Rl78y/4XrbxwOFzRFSBOcA8//HBJSJ+1mAWTBx98kD7ykY/QX/7lX/J+3XTT\nTdTR0UH79+93xfZoF/O9FPF4PNTW1kaDg4N0zz33mNwl1kmFKddwOEyRSIQURTFlrooVm+zGzDAM\nCofDvF3r94lRDXR1dfG3ELvwSsb/Dyy4iipxFl0NkUpdyqqQxsZGkwI0DMOkuDs7O6mxsdHkLvD7\n/XTPPffQPffcw7eJr73WTEj2v/UH68bKY0qjnMVpdTkAC8qAxWMvR9yyVZmJ5FVMgYmTQjQa5VWL\nRBcCK9nGkqjYmHzrW98yjdeePXtM1nEtRFEUuvnmm03bWltbTROex+OhnTt3ErDgKnEaa/H56LpO\nuq7TO97xDlIUhSt9Ubmz5x4KhSiRSJT9rqiqyuPxRRZQMZt3JUQqdSk1FeYfZUqlvr7e9hX5k5/8\nJLew2UKU+ANNJBKOShwwW/Z2P8xqLCm79HTWhtUVIxJpAaXrBNUIU2JWFwdLXbc7RxyTzZs32/J8\nMws7mUzS7bffztkx2fU2bdpE9913X02/Jx6PhzMidnd384VU9uYiMipaJRAIUF9fH/X19ZHP56PN\nmzdznvZgMEixWIy7psSapeLkz8acveW0tbWRYRjc+LDSGbPJlrly4vH4ilnrbnWmDGmUkJCQWEuo\ntSUuLfW1LYZhlI0G+fSnP027d+8moLK7RFykErcpisJdENaoiGpZGlkRBdZ3uz44LSoCpYuZ1go8\ndm36/f6SKkRu+smItMRz/X4/t3bZtdlC9eHDh+ljH/sYdXV10a//+q/T7t27eXWkWkoul6PDhw8T\nABNnubXCUjnRdZ23w9wibHFUDPFUVZV/30RhfDHKFS55xnHj9/tNb5LW9ZKVpAyQlrrEqkBvb68p\nrd2KF154Ac888wzPHCyXfMO2T05O8v+LxSKICJcvXzYdw8C/6KrqimqA1Z4EgJmZGaiqajpHTKIS\nE5ZUVYXP58PU1BSmpqb48SydnR3L2mRJQoqi8MxHBpZw45QQlclkkM/nsW7dOkSjUezatQv33Xcf\nvvjFL0JRFPT390NVVeRyOTQ2NuLJJ58EADz99NM8S9IwDLz3ve9lhlPJGK8kWOITAIyNjQFYeG5i\nMpdIg8A+Dw4Owuv1wuv1Yn5+HsPDw3jqqacwPDzMk5wSiQSOHTsGr9cLYOH+nnnmGYRCIQALVBaG\nYcDv9+Pll19GJpPB7OwsLl++zJ/l2NgYp4koFosIh8NQFAV+vx+FQgHRaHQlhsk9am2JS0t9bYjP\n57ONvujv7+fV6YFSH3dra2sJGZXba+q6zivoeDweampqMkXA6Lpuilqwu74bsbOu2TXFSIlKiU9W\nixywt/REvnK3IlrobFskEuF+9ZaWFj4WDQ0N9M///M/0p3/6p9Td3W16m6gVWZWYoMS+F9u2beNh\nsOxZs/3WGPaOjg5KpVKm582ohK3Ph22zvtXFYjHyeDyuxl7si9uwy6WKa51Za6UtlfrakMbGRnro\noYcoHo9zxZzNZm2zQUXlJ74aVytOGZqpVIq2bdtGHo/HlkO7WpcMi112G00jJq+w863Heb1e2wpE\ndiGUYp+tEyALydR1nRRF4Yuhdpzln/jEJ3jd0MHBQeru7iZVVU00xrXKmLz//vvpyJEjZBgGZTIZ\nTr9s1x/movF4PI7JXuJ5bNJqbW3lXP3sO5pMJskwDNMiucfjMUUfGYbBKX3ZfnaNaiffpYhU6lJW\nVLLZLPdlsh+M6BMNhUJV06uKbQHOvNeiMKUGmMMC4/H4slhU6XTaNFGwH3UwGCwJixT7yJQsO9fv\n99PevXupq6uLW4zVVtVhURy6rlMkEqGOjg6KxWL04IMP8oiSRx55hBoaGiibzVJjYyPlcjlqaGgw\njdNqkM997nN0+PBh8nq91NHRUTLZiVEw4veIrW/09PRQMBgsW8HI7ntl9ZGn02kKBAImg4E9Y/G7\nKE6EbssPLlWkUpdSUxEtTmvdS+sxYi1K63ENDQ08q9GtiFaqnUuknKWuaVpF68vOCmYilm6zux+g\nlKtbVAqqqlI6nTZxn9hNRk5vKR6Phy86Hjp0qOQ6qqqW7X+tJJvNlrhg2PNg//f395cobXFh2o3b\nSkwUY3QCbDwYf4z1nA0bNvA3Ifb8xGdWqWDLcolU6lJqKuzH5/V6S3zJ4v+s0IKouDRNo0QiwS3t\n5uZmk7+zkvtE3L8cafpWsfbXjkCqHPlTJd97PB4vsdqt7hdRObFxFt9MWMWhhx9+mCKRCH3iE58g\nRVFoYGCgpLLUapD77rvPVOBCVLCRSITC4bCt8mR0Em6I3JjCT6fTVFdXR11dXSVVrhRFoXg8Tu3t\n7fwtwPrW4Pf7qaWlxeRqXAmRSl1KTUXMELUTUeFt2bKF6urqKBAI8HRw8VjGvcEs3Gp94tWI9Qds\n5fhgTIDWtwdFUUyp++JbiPUa4uIdC6Fzc16l8TQMw+QCisVitGfPHhoaGiIA9MADD7guF7fS0tPT\nQ9/97nfp4MGDdMcdd9Cdd95JGzdu5D5w4O3qWcDCuklXVxd5vV7TWLGsT+vbEhPr+Ngls7G3JZaE\nFI1GacOGDQS8nWTGjBUAvJqU9Q1osYyhTiKVupSaiMfjob/6q7+iPXv28PRuJ3Fr5bDF1sUuTLGM\nUKA04sEqbvza4o/X6ke3EpExS6/cAu26desolUqZlIDH4+F0r2JbrDZnuf5/4AMfoKGhIRoaGqJD\nhw5xC361KnQm//RP/8T/r6+vp1/91V81EcMxzhhrNFWltzZgQQmHw2E+Afj9fh7jL7pWWGk+9mzj\n8Tg3Jvbt21eWyIu17fF4Kn7PFiNSqUtZslSq9WknjIubJefs3r27hKxKVLLAgnuFKTQWhSBGNdhZ\nXeFw2BSFYJfCX0lEila2kMrqeJZro1z9SiZsodKapMQUspOvPxqNmsZcDFMUJwZW/Fk8n/GT1NXV\n0Ve+8hXq7u6mf/mXf6E/+7M/oz179tT8+1RJbrvtNvrt3/5tCoVCNDAwQIODgwQscLq3trZSNBql\nu+66ixsLTkRedgvP4lglEgkTkZldGKdhGDxMl1nrbDIRj2dvkMlk8qpHDkmlLmVZxKowK4lhGLRu\n3To6cuQIAQvRKH19fSY2ROuXX7RqrFS4TMm7jZ+2RjOUE2aVib5ot+Km4AU7xvqjFy1DcUyYwmcT\nAfMh28W3V7r/O+64gwDQl770JfrDP/xDU/z+apZnnnmGPv3pT9PHP/5xE9FWa2srbd68uSTvwE6S\nySQFAgFSVZVPZmxcbrjhBvqN3/gNCgaDJW4v9h2zur4URaFsNktdXV3U1dXF3xyt7hZG/CVuc2MA\nuBWp1KUsq1STlPLwww8TsGCtsvOY5VqpbfE1mG1vamqiaDS6JFY8VVX5jzUSiXAFysLj7NLSy01o\nVvIvO6XLtjGqBEVRKJVKlbhiRJeS9R6Z4mDWuRhe56ToFUWh22+/nbZv304A6NZbb112/+5SJBAI\ncGvZ2q9QKERExCN4PB4P5fN5MgyDW+bbt2/nhgCLmIlEIiUMoE7PA3hb2TY2NlIsFiNd10tI55i7\ny+qSY89AdAOJxgT73i6nQgekUpdSI/F4PNTX18d/dOxLLibksJJoVnHzI2A+0MX2T1Sa4o9SFNEK\nL2chR6NR/mPu7e0tyeYUj7XylrMFUjbZMAuvqamJMy6yScjqfhHHSoyGYW34fD4aGBjgjIVsf62/\nG6y/jz76aMmzjkQi9P73v58A0Gc/+1n6/Oc/T5///Of5uIkTXzAYtOVdT6fTrowPtqDNvpNsDGOx\nGOVyOUomk7YuM8Ds8mEhlIyznbV1tcZaKnUpNRHmZmFVZICFH5FdMYpyCrNS1aFK7girS8Xph2ZN\nrXdq2y5EkkVahMNhXmyBKV6Px8OVsvWVvK6uzrTAarcAGg6HTYtyTrHl4jlMoUWjUVPM9+/8zu/U\n/HshPodyFMk/+9nP6FOf+hS9853vpGg0Snv27KH777/fVdtsTKPRaMVSc8xPLn4PxDH87Gc/a+pr\nQ0ODqc1MJmP6jovnsmfiNhHKrUilLmXFZf/+/WX90+V+aG7dO24XbkUL2tp2NpulbDbLo1IYf4y1\nDat/X7QuWQk+0YK0Xicej/Mfdl1dHfn9ftvFPXECY4udwNvWaaU3GJ/PR+l0mjo7O+nGG2+k/v5+\n6ujooFwux11IKxlPXa2I48ws5L/+67/m49He3k7vec97Sopei1Iuw9Pj8fBFcfG4bDZLgUDAdDxj\naIxGoxSLxSgWi1FnZ6fJtdPc3EyRSITXLLV+B9h3abm51qVSl1ITicVipkVBpyQg9rlaZbOYGHXr\nNZhvWlEU24QWVVW5n1V091jDKe14a+yIzZjvOJ1O07p160o4X1gFIxb+WKnuJxPmPsjlcuTz+SiX\ny/F6nLlcji8SriQ/STXi9Xrp8OHDlMvlTEXKDx48SI2NjXTkyBGu8G+66SZ68cUXua99+/bt9N73\nvpcGBgZoYGDAceKzjiWb4ILBIIVCIQqFQpTP5/mzNgyDu9/EdR1N06ihoYH8fj8f70wmY8pOZVw0\n7FmGw+Flzd6VSl3Kikt9fT3lcrmq06bFMmOVZKmWj6jgrXHh1gLYorBEFOv2UCjEf/jZbNbRKrYu\nzLI22f3bvam0tbWZznNyXWzatIn6+vr4PbCszO7ublfRIrWQgYEBzoHu8/noIx/5CO3fv5+2b99O\nzz//PN144420fft26u3tpWg0yhUqsEAXEAqFOOdLT0+PaeJirj6/3296C7N7tmxdgz0H4O2EMxZW\ny9aHxOiYaDRqWkBlYbDsTczn81EoFFpWXhip1KVcNUmlUryor2EY1NraSh0dHTzjT7RgnQoqi3HY\n5VwvYqRINeGK1Yi1xJnYH+amsWObZML6FYvFTPH1zF3g8Xi4ZQgsKA9WRk4siCxalZ2dndxyf897\n3mM7dq2trZykixFe+f1+amxs5NEy5aKOaiXBYJC+9KUvUS6X4xFH27dv5+sAt956Kx04cICampro\n0KFDlEwmuSUuTpipVIq7SJhFzya9Shw3uq6bop1YsZBkMknt7e0Vv2MsfFFRFJ4zUVdXx90yAPhC\ndSX/vluRSl3KVZNNmzaV8IfEYjHy+Xyc09zv91NnZ2dJ1XurYnZK57YTptzLTQJLqeQjWussBZ3t\ne+SRRyr2rVyyVk9PDwGg3bt383atIZQej8dUBxN42wfc09PDCyqL95/L5Wjfvn2k6zqlUilupe/f\nv79iRm8tRFVVvoA7NDREd911FwELljt7yxCfJUtAYmJ982ATQX9/P7eSrW99Yv1Wu7cov99PmUyG\nNE2jvXv38smVZZQCb4fVis/WOmmIfne7t4KlRsW41ZnKFcW5anFlECVWGSKRCK/4EolEeEUdXdd5\n5SAAyGazOHv2rOlc5Up1HSJCIBDA5ORkxeuJ5wCAqqogIng8HuRyOWiahuPHj8Pr9WJ2dta2jXL7\n7BAIBAAsVBo6ceIEdF1HoVBAd3c3fvGLX2BqagrJZBJnzpzhfVTVhWJirHoR66uqqigWi7xyUiKR\nwPj4ODKZDH7xi18gHo9jamqKV0FqbGzE7OwsCoUCRkZGoCgKr/6TyWQQCoWgaRqam5vx8ssv49y5\nc5ibm8ODDz6If/iHfwAAtLW14fjx467vd6Vw66234t///d+hKAr27duHS5cu4fTp0wAWxvDs2bNQ\nFAVdXV0YGRlBKpXCq6++yitKpdNpzM7O4tKlS+js7AQAHDt2jH8nU6kU5ufncfToUSSTScRiMbz5\n5puYnp7m359QKITx/5+9946Sqzryxz+vc849PR2ne6a7J+ccNaNRQqOIAkLkYATIa3BgWbDBYBub\ndTj2frF3cVivvT7H3jVevPzMOmEbDAbb4DUIBJYlGVkogHIYhQmaqd8fTV3ue90zGoEIuzvvnDoz\n3f3CfffdV7du1ac+deIE/H4/jEYj9u3bB6JctSVFUVBbW4vNmzcDwLRjxuFw4OTJk5D1qKIo4rPd\nbofNZsPp06fz9jvXjYhmVpbq3bbEZy31966w5VfoN4fDQel0mtLptFheut3uswaGZEtppux6QH6A\ndDouFXkfu90+4+Uvn68Q0dNUVtZM6mhaLBbh82W3FZCLQTBZmdvtprq6OgJyFir73k0mk7DG+Xwy\nzr+5uZl6e3upqqqK1q5dS83NzbRw4cK8jMn3inz2s5+lNWvWiP6MRCLU2dlJ//Vf/0WVlZUUiURI\nr9dTOBwmg8FAq1evFnEFOTCpKAq1t7fnxTB4pcaWMrvCeHXj8XiEtW+326m0tJTC4TCZTCbxLF0u\nVx61bqG4hzbYr10FcIwFyA/YvhmZdb/MypuWSCQilsNFRUXU09MjXrZrr72WHA4HGY1GikajFI1G\nyev1qoiXent7VRhrrU+cReZuma490ynvqdA1DQ0NedcrlK06ncjHF4oNGAwG0ul0BRW+TAzFIisK\n2e3E1zEYDMJ/zpOd1s/OLq0rrriC/H6/4CE3mUy0du1auuOOOwST4HtN3G43/elPf6IVK1aQ3W4n\nnU5HiUSCWltbKRAI0KWXXkrLli2j4uJiCoVCVFpaKmCZ8jMs1N+NjY0icDoVKRtz61itVkokEgKJ\n9MADD5DJZFJBJeXx4ff7C44Xn8+n4g8qLS3NAwmcK83GdDKr1GflTYlOpxO4Z4vFQtlsloxGI/X1\n9amIrlpaWgTtaSHI3HRcIxzE01bfmQo1c7YXYyrFXkiy2ayKJqDQ/ctKf6ap3kzFq52AtBQIU2Uq\nyvhmo9EosiPZjw6oSc6AN0inMpkMzZ8/n4DchCxPsO8l8Xq9VFFRQclkkqLRqMD5l5eXU3NzM0Ui\nEUqn0wJtkslkRAB0qhUR8+7bbDZqa2sT/VdoLHBgv7S0lIqLiwuOqXnz5on/GW3ElMbaeA5nA5eV\nlVFRUZFA8vDvvNqQ34W3EuSfqc7MOQBnt9ltdpvdZrf/Hdu7bYnPWurvbdHpdLR+/Xrq6uqi2tpa\nqqiooI985CMEQGVF8r7ysXPnzs2zUNjSYd+nFk0QDAZV0ECZuGoql8lUPvPp0v21wtZUPB4Xqf9a\nvpapziGvVJLJJCWTybz9p6IGlrNa5WNkbhe3260iENPr9RQKhSgajVI4HFa5aL797W/TBz/4wTxu\nmPeCDA4OinJ/nZ2dwret0+mosbGR0uk0dXR0UFlZmSiqXVpaKtwiZ7uX3t5eMRa0sRruf14Nas/l\n9Xqpvr6egsEgOZ1OslgsYgzKrJrsw1cURVQ/4lUVV0zi8zmdThEbCQaDs+gX3mbRL++Nbf78+TAa\njRgdHcWzzz4Lg8EAk8kEIBfh37p1K0/C0Ol0sFgsOHXqlEB9yFs2m8XWrVvzrqHX61WoEd78fj8O\nHTqUh6wB3kAa8F+v14sjR44U3AcAjEaj6rfx8XEAgNPphE6nw7Fjx/KubzKZMDk5iYmJCRDlEDdW\nqxXHjx9XnRvIIVMAYP/+/apzMMrHYrFgZGQEZWVleOWVVzA+Pi6QPY2Njdi8eTPGx8fhdDoBAESE\nkydPQqfTqe6d+yQajcJisWBwcBC///3vUV9fj1QqBbfbjUcffRSPPPKIQNS829u8efOwe/duvPzy\nywJRUlRUhKKiIhw+fBh79+4FAMTjcezevRsmkwmjo6MYGBjAo48+qjoX93s0GgWQQ8Q899xzM2qH\ndkzq9XrcfPPN+Nd//VfodDqcOHFCIGwA4OjRo8hms9i0aRMURYHX68WhQ4eg1+tht9tx/PhxWK1W\neL1eGI1G7Ny5E2vWrMFDDz0knuOhQ4dUbTAajbBYLACA4eHhGbWbZtEvs3I+pa2tTSBh5Kw5i8VS\nEMGi9VmzpTOdZa/dX7amZlK1Z6Z+cPatFvLTNjY2inYWStzh9k+Fl+c4w1QcOB6PR8XzMh33DN8T\nB2SZ3oBXFdlsVpVg5PF4aP78+VRRUUGlpaV0//33v+vjRhY5Ka24uFhFgPWJT3yC5syZo+pXDibr\n9XoKBoOqMcCUuHV1dQI1JOdOyONyuvFw5ZVX0o9+9CMCctZ1IpEgu90uKh5ZLBZqaGigUChE6XSa\nUqkURSIRgfTS8sZYLBa68MIL81axiqKQz+cji8XyprntZ6wz322lPavU31l5M8txWUGHQqFpuUQ4\nQ7QQK2N1dfW0POByG1nOlWZ3Oqijy+XKm0hYUTCKgVkbZaVsNBpVfTATiKTH48nbTz4n07vK5dX0\nen0eORS3l5WIzK8OgGpra+mGG24gq9UqUC89PT3k8/movr7+nHjw3y7ZsGEDbdiwgerq6igQCBSc\nzLu7u0XbY7EYxeNxslqtquB5Op1W9aHP56OhoSEaGhoSz09+7jIypZB0dXXRbbfdRnPnziWHwyEC\n+EAuMYrPrSg5rn12sbhcLoHuSqVSqgLZfP2GhgZVcRN2vbwVF8ysUp+VPJmJQp1KAoHAlPzjLHxu\nt9utehkZQfBmoF3FxcXnXJmIr6N9gbSf5aw/Vn68CpELXXM7ZN8+/y+zKhYSmamRicK0aB2HwyEU\nAvtsZ0KJYLVaqba2VtXO1tZWuuCCC0R6/fnmHzlX4XtzuVyUTCZF2UAg59+OxWLk9/uprq5OoF54\n8ufVCfcD/89wR3mlJfOuywihQhnG8jjka/p8PgqFQiqoaTabFTkBDQ0N4tnzZClP9DzedTqd4Ozn\nCkznK64xq9RnpaCcC8uh3W4nv99PixYtElV0ziYcJNQSZzEXh/wiyPuwYiqkgM5mcRW6P9nFIf+m\n3T8Wi1FDQ4NQBNPBKqe7bqHVi6z8S0pK8uCNDNfjtmrLq7FoebvlfYLBIKVSKVHsuK2tjS644AIC\n3qC0DQQC70o5O71eT319fUJB9/b2qopgy0RoXq+X3G63KH3o9/vJaDSqAsQWi4UWLVqkKhjNv03H\nzdPZ2SnuX57YtcZCZWWlmHS9Xi/F43GKx+PiOrz6DIVCVFNTk4eHLzS5a3M1ZDqJc+3PWaU+K29J\n2PJxOp3U3NxMsViMEokEKYpCpaWlqgpCWsv4zjvvJCAX8dcqKv6/kPJnpAEAQdQk+7DPpf3aF6cQ\ndllW+F1dXQLD/qUvfUlcl0mabDYbFRUVqSYlbdyAfaoy8oSVPSuVRx55RHWM1+st+JLLk4Tcv3wf\nsjWfyWSExWk0GumCCy4QbSsvLye32/2uuGECgUDehFxfX082m03wA7FlvWLFirzxII+VpqYmqqio\nEEgfudoQn5fdM1o0kdYNVltbK2IngHpCMBqNVFRURNFoVOQr2O12amtrE1S9zLXOz1zbViC34tPy\n8b9VmVXqs/KWhGGFwBvZlGw1FXITsOLjF41fvmQyqVJYU0H75M9atsPpRJuqLYter58SlgioX0hZ\nCfh8PsFNPtPra0VLZMaJKevXrxff2Ww2lQuoUAENWVipAG9MoExEtWDBApo7dy6tXLmSAFB/f784\nLhAI5BGwvd3idDrFGKipqaGamhoqKSmhkpISWrx4sXBntLe303e+8x3Bk86BYL1eryIkk10xiUSC\nvF5vnkItLy8XxGnyGLBYLORyuWhgYEDEJIxGo5h0ZOoGFqvVSsFgUPUcOdOVqybJgVtt1uvbUZRk\nVqnPypuSRCJBa9asoaKiIuFf7O/vF66EG264oSC3uMPhIJ/PJ6yeqqqqKZfE/DLKy+fzRU+qvQbz\nv/D/2gCu7BuXv+djWBnKSv9cfdSswDi2IPtt5UmHlaBMG8sWOLeV8dFGo1HU00wmkxSJRMjpdJLZ\nbKahoSGhcBYsWEAA8vi/3ylRFEUUsrBarWIFEY1G6dprryWLxUKdnZ2k1+uF24ilurqaGhoaaN68\neRQOh6m6upqKiooE2gXIuUwqKyunddHxqk/bLu0xsktHft5c1EReGUzFu3+2vngrfTmr1GflnMVg\nMKiquANvKLtAIEDLli2jK6+8UvhG+/v7qb+/n66//nq6+eabVeeSCzoUWvoXQrUEAgGqqakRFKfn\n4v+fSrRByekSkuRl+0xQN4xO4ftj6l4ZWjmVxSZTLhRqi+zaKUQGZTAYhMJftWqVqk0AxIrAbrdT\nZ2enin72nZB169bRd77zHdV3y5Yto1AoRIFAQFVdiN0UPp+PWlpaaHBwkAwGgyhEzcZBofJ+dTst\nDAAAIABJREFUqVSKUqkUeb1e1WSpjV9o26ctniErdB4HhTiCZjIeFUUpOPG/1YD1rFKflRmLxWIR\nvl15YHLmH38XCATo6quvJiC37F+yZAktWbKEOjo6KBQKUWNjI1166aV0//33z9iHq9frqbS0lFwu\nl0p5aQOezOvxZkV+GbV+bwB5POUACqIb+H9Z6csB0emua7PZhLIA1C4jOSAIFIa+OZ1Ocjqdol2c\ntcikV/F4nFwuF/X19VEikRDB7d7e3ncUAcOrG51ORxs2bKClS5fS0qVLqba2llwuF11wwQVUVFRE\nyWQy7z7Zou7r66OFCxfSrbfeSgAEr7rcZ6lUSoyTqZBNb8Uo4JwDPo+cIaqV6dx850tmlfqsnJNM\nFZDk71OplHixplLYjCYodC7ZGtZarxz0SqfT5Pf7C7Ir6nQ6Vem4mYqiKCLNXLaojUajikVRDqTy\n6kSmMpgKM6+9R046kZUMVyWSJRqNigQa/k6n01FlZaWqfBpPGFxCjRNe+Lh0Ok0LFy4U1+NEpLKy\nMspms1RZWUmZTOYdKTzN16ipqRHfaVcZH/zgB8UEnclkhEulEPTwxhtvJACi1iq7zrgOaF9fX94Y\nAXJBU9kKl5PIOCjNSBemhdBem8eINsBuNBopm83m3ZcMLJDzC7TyVgLWs0p9VmYkDQ0NeVmeWqtu\nwYIFwlKRi0pr5WzZljOR6SwrnU4nFN5UL40WQgbkJhuZ85p/q6qqUuHBZRw6K3Zte1gB8L3K7eDE\nJUVR8ihjdTpdXpWnqWCG0WiUSkpKyG63q3Da8j2yUvf5fFReXi6YClOpFHV1dVFbWxv5/f5zrhf7\nVqWurk6gngwGA1VVVdGCBQuEb7+uro4cDgf9x3/8B5WUlJDP56OGhgbBnxKNRvMyQOvq6oRiLi8v\nJ4fDIfYpKioSPOvBYFD0F1vqnMXq8/lUyluv19PGjRsLjjF+NvKkqn1ubW1tKuucr9vU1EQmk6lg\nRS/tmOW2z7RvZ5X6rJxVfD4fNTY20urVqwmAINCS93E4HKogos/ny1PYWl70c/Fjz0Sm8q1PxWVe\nSAqhP/i8hZbOMhLlbLQDMslTod+1k6Z8P7L/Vj5Gm+hltVpVcYri4mIqLi4mp9NJPT09tHDhQpWC\nyGaz1NTUNGPq4PMlHGCPxWJkMplUkwrHXRwOB73vfe+jTCZDN9xwg2ol09raSk1NTRQMBlVxAKfT\nSbW1tXT//feTwWCgZDJJsViMwuHwlKghhhcyrBOAWOkwuoWfARfGkMeTtgCHLMXFxRQIBGj+/PkU\ni8VE8La5uVm4xwohYt4KMmZWqc/KtKLX66mnp0d8ll8gHoxOpzPPBcFoEnnwy0pKq2TPxWKfqVVZ\nSIGe7TraDED5Ph0Oh1jaT8XFPdWLOJ3StFqtKqTGdOfjAg+yz9ZqtYpVhtaXy0pfrusZCAQokUhQ\nIpF4V5KNAIjgqM/nI7/fTx6PR2WRKopCDodD5b647777BLpk7ty5pNPpaGhoiBYvXixqmMqW8ODg\nYN51eVzK8E1W2larlUKhEBUXF4uAKivspqYmkf4vn0vuPy3eXHbFXXHFFeLe1qxZQ1arlbLZrCgk\n7nK5Cj6LNwMxnVXqszKlGI1GSiaTQomyQiyEOFmzZg2ZzWYxsGdqYV9xxRXU29urSq/XivZ7i8Uy\npeU9laKVrWB+iaeiV9XCGQ0Gg7DgLBYL3XTTTeL7qa47HarC7XYLuCf/ZrVaBUJGW8oPgFA0/H1D\nQ4Mowbdq1SqB/y+UsWqxWMjj8YiJg10OBoNBVLJ/pySdTlNDQwPV19eLfuTCHfKYuvLKKwlQu8R6\ne3tp2bJltHTpUrr77rtFIhKLx+MRJFuF4i187kwmQ7FYTFjorExLS0upvr6egFwAtqioSPjzGSo5\nk3vUwl4jkQilUimaM2eOuLbMQcPjiPM8+Hg2SrSkX2eTWaU+K1NKZ2enqADDA66QzxmAqjZmoSAq\nUwDw8czjkclk3tTS3+FwFKw9eTaZauKIRCIqsi4tyoSFXzj+PZFI5KWRyy81+4wLpfhrRb4P2Ycv\nwyFlYQUkY9R5BcH+dMa88z02NjYKxZfNZt8yFPRcxev10uLFi4WSYq50JrxiTnK3200bNmygjo4O\nCofDYnxFo1G6+uqr6aMf/Sg5nU6qqqoSK5CKigoKh8NiPDmdToHskcdqKBQivV5PVVVVIkHJ6/VS\nIBCgxYsX0913300lJSXU1NREfX19VFdXR01NTRQOhwXUshAccboqWRyI7e7uplgsRnPmzKEHHnhA\nJH8ZjUbyer3U3d2dl5CmhUzKGdWFZFapz0pBYWUgW60yOkAb6TcajQLWyNl+bOVrFS8P0Lq6OlWw\ndKYKhlOwtd+fi4KSA1v8cmqt/7lz56oKePC9KYoiiMe4T/geDQaDSGIpLS1VMfDNpI1sxcvflZWV\nkdVqFQFWrrMJvIEg4YzRgYEBAbHz+/2USCSooaFBoGiampqooaGBkskkdXZ2vqNKXVEUWrBgAZnN\nZqqsrKSWlhYKBoPCKme55pprqLa2Vnz++Mc/TsXFxTRv3jzq7e0lAHTVVVdRIBCgyy67jADQokWL\nKBgMChcHT1hGo5G6urrE86msrCSTyUSpVIpqa2vJbrdTS0uL4JMBIL5Lp9NkMBios7OTAoEA3XTT\nTdTe3i4mHrPZPK1vXZ5sgRxd8+LFi6miokK8Vzz5hsNhKi4uVqFsOIuVaRL4fDJ2Xq/X5yWLzSr1\nWckT5ojmzxx8k1ErWhcMEzF9+tOfplAoJAZgIBCYEh1wPoQDgVarVeXOOBeRLS7tiwi84ZfWIl14\nMmJlqz1OLlCsFTmYycKB0EJBMpkwii10IBeoXb58Oel0Ourq6qKWlhZReBoALVy4kICcoiopKVG1\niZN23ikxmUy0ZMkSKi8vF66v4uJiWrJkCX3yk5+ktra2KfMMuLarLB0dHdTf30+XX355wWOYlpdR\nMTwBh8NhkYhUXFxMJSUlwspub2+ncDhMg4OD1NzcTCtXriSXy0VDQ0NUUVEhXDx2u10V6OTVBV+b\n+e21z9xqtQrrXH7GjIJJJBIUj8fFuM5mswKiOtMV7axS/z8iM3VR9Pb20tKlS1VBG7vdnucjlpW5\nxWKhL3zhC7R27VpyOp1CWQwNDRXkS5+p4i00cUy1D1vEZ/M9aq8tY6VZpsKZr127loqKioRCCoVC\neQWegTcsqemCXIWyEOvq6qaErslLcp7AgJziqqysFG6MpqYmqqqqEhBBPmZoaIje9773iXuZCvP9\ndojD4RD+6v7+flq7di15PB7hNtH6qtnHDqgn3GXLluUhkFixDg8PEwBasWIFVVZWCvdYeXk5LV26\nVND62u12qqqqomg0SoODgxQIBOgjH/kI3X333ZTJZMjj8VBPTw9VV1eT2+2mK664ghobG6murk5g\n+mXyMxmeym1taWkRdL9y4Foey9MlyRUVFVFXVxdFo1Fat24dbd26lbZu3UptbW0qGmGTyUSNjY3k\n8/nI7XaLcTtTnTlbzu7/0NbU1ITNmzejqKgIOp0Or7zyCuLxOPbu3SvKe/F4UBQFer0e7e3t2LRp\nE5qbm1FUVISRkREcOnQIzz77LE6fPq06v7ZMmHZTFHU1LiJSfUdE4hz8PREhGAzi0KFD0557quvJ\n90NEKC8vx5///Gexj8FggMFgUJV8MxgMcLvdogSZoilZp93kMns6nU4cU6g0X6G21dXVYefOnTh2\n7BiCwSAOHjyI8vJybNu2DZlMBlu2bMHAwAA2bdoEAFi0aBF27NiBAwcOIBaLYevWrRgdHcWJEycw\nNjaGyspKvPTSS+fUVzPZdDqdbGxhZGQE999/Px544AEYDAbs27cPu3btQjwex5YtW0R5QoPBAACw\nWCy4+eabsX37dvzbv/2b6txyHzocDvj9flgsFoTDYZSUlODb3/62aMPk5CQqKyvR0dGBxx57DECu\nBN7jjz8OAHC5XPD5fDh9+jQaGxvx4osvwul0Ih6P49VXX8Xw8DCeeeYZ3HXXXfjud7+LpqYmvPba\na3A6ndi+fTvcbjfOnDkjSh9u27YNJpMJwWAQp06dgsPhwK5du0TbzWYzRkdHAQCRSASKomDPnj0F\n+zCZTIKI8Morr4h+vO666/C1r31N9AOXTeQ+47FJs+XsZkUWk8lEdXV1tG7dOuGvjMfjeXzjbK3a\nbDYRRAVy1uuXvvQlsaz1+Xx0ySWX0CWXXJJ3rTeDS9e6fgohcc5VtOgeg8FQEDZZCEfOxxUqlqH1\ndZ5tJXE2/myHw0HV1dXkcrnEtWw2m/CRA7lAIsMV2ZJjq1VGi0zHK34+5LLLLqPrr7+e2tvb6dvf\n/jYtWbKEgDdcWT6fj3w+n4pCWeuSWrVqVV58QbZUzWYztbe3i+/YeuZzut3uPIu4q6tL4M1lX3Zz\nczN1dXVRa2srORwOCgaD1NraSj09PXT11VdTcXEx6XQ60b9c5jASiQh2yXg8TjqdjgKBAJlMJorH\n48KVFg6H8wKrbrdbBTDQFiJn4UAuUJhvX7v/THVmzqyY3Wa32W12m93+d2zvtiU+a6nPXKaC481E\nSktLyWKxUDKZFLUf29vbhVUgWwbaDL2vfOUrdN1111FzczOtXbtWZU3wcXJatJwtKf8/07YWstLl\ngO5MJBAIqJAWMxFtQpXWApNXMixaq52DbbJ1XihAKt8fl1LT6/Xk8XjI5XKJGqPt7e30hS98gZxO\np+AjB3IsjC6XS/jPn3zySVIURdT6PN8SjUapp6cnryj0zTffTD09PdTW1paXpNPW1qZaOcgJajLf\nO5CzztesWUNAzoKtqqoSK0Wv16virzEYDAItw5JOp0V8gp9JeXk5RaNRKisro3g8Tnq9nrLZLBkM\nBnK5XDQ4OEi1tbWi3SaTicLhMHV1dVFtba0ABhiNRgHRzWQygj5Zm22tHReFSMgKCSdTMcJqqv1m\nfeqzG1atWgWz2QwA+NWvfoXXXnstzy8KqH3hPT092LNnD3bs2IGenh4cPnwYfr8fAwMD+OlPf4pQ\nKIQf//jHBf3Fsh98uu/OZdPpdLBarTh58uSU+8g+Tfbj8hYKhbBv3z7RlqamJvz3f/+3+Mztcjgc\nOHHihKrdss/fZrNhZGQEiqII36+86fV61T0W8v/b7faC9+Hz+TA+Po7R0VFMTEzAZrPBbDZjZGQE\nPT09eP7557F06VI8+uijAIBEIoHHH38cY2NjuOOOO7Bp0yb8/Oc/RyKRwK5du/JiHedrW7t2LXbu\n3Im//vWvuO666/Dwww9j586dsFgsaG5uxsMPP5wXw9Dr9SgqKgIAHDt2DCMjI5icnERpaSlefvll\nAOpn9olPfAK/+tWv4Ha78dBDD8HlcuH48eMAALfbjWPHjqGoqAgTExMi5sGbyWRCOBzGnj17EI1G\nceTIEcTjcRFvUBQFR44cQSqVgqIo4hkFAgG88MILCAaDGB4eRjQaxb59+8S7YzQa8ec//xkejwcn\nT57E+Pg4IpEI9u7dCyA3Nk6dOgWTyYSxsTExHn/xi19g3rx5Z+3XsrIyxONxPPHEE5iYmFDds7yd\nN586gAYAXwfwEoDnAbwI4B8ABDT7OQB8GcCW1/f5GYCqAuczAvgkgD8BeAHAkwC6Zy31s8sNN9xA\na9asmTKdXrY0r7vuOlVJLnk/OTtRtrQ7OzvFudvb2+n9738/3XrrrdTd3S2q0BSCoE0lb7YWo1bM\nZrMKSz/VtTijUs7QlFEV01EJ9PT0zHhVwSuGcDicx3szVR8wmkIm+urq6iKn0yksuTVr1qj4xbu6\nuiiVSlFZWRllMhkBgSsuLqaHHnqIiIguvPBCam5upvLychUlwbkW6z6bGI1GuuSSS8jhcFBJSYlA\n4NhsNqqvrxc8Mwwd5XvkJLfS0lIKhUJkMBgoEAhQSUkJrVu3ruC+TFkRCoVozZo1ovaqdvzKfa6N\nhfD3kUiEOjs7xYqGff+1tbUqeGgikRCIqSuuuIKqq6tFLMBsNpPH4xHvQDabpc7OTuFn164guToS\nkMtyjUajKkitz+fLWwVGo1HRfs4o1j6DGXs3ZqDUtwB4AID19c8R5BTynwFYpP1+AuBx/g7AJwDs\nBxDRnO/+18/pf/3zNQBOAqifVepTSzAYpN7eXlIUJS8zTSttbW1ks9lUEDK5coy8r8xIyINzw4YN\nKshiIBCgD3/4w2S1WmnOnDmqZCSr1TrtkvHtwLAz3E2n0wn4HCeIyC9LOp0WSofbqOXhkJfGhTjV\ntcLnl68zHXOlVvEAEEqCIZuc9BKJRMQkcf3114sJ1mKx0OLFi6mvr4/6+vrI4XDQ0NAQuVwukTn5\nZirxnIuYTCYiIqqqqlIFZi0WCyUSCcpms2S326mrq4tisRg5HA7KZrOk1+tF8LRQUlRfXx+ZzeZp\nXWvhcFhgxYPBIK1cubIguyaQc7nwc4zH41RdXU1er5dKS0tFUll5eTn19fWpXEM9PT0UDoepqKhI\n5BVks1nKZrPU2toqyt+ZzWbq7+/PS5LTJqMZDAYV0IAJyYCcUq+srFQdX1xcTBaLRUz+hfrjfCr1\nlwCUar67GsAkgAtf/zz/9c/9Gov8EIAvS9+VA5gAcKXmfJsBPDyr1NVSXV1NXV1dZDKZBB6X0QbT\nSTwep/vuu4/S6TRVV1dTdXU1hUIhWrt2rZgYeKBxFp6spBobG+m2225TlfsqLy+n++67jy6++GIK\nhUK0evVqUaZM5ifX6XSiqs9UvsRzKV2nTczgY2Xly8pPtspjsZhQ+qtXr1b5e7lIhqwITSaT4Oee\nqt2FCjjPNE9Ar9fn0bHqdDryer2k1+uppKSEIpEItbW1iUkrnU5TNpslILf6kClslyxZQitXriSH\nw6FSHm+HcP9WVlbSkiVL6Itf/CJddtlldN1115HT6cyrRNTf308rV64UeO+hoaGzctHwfQKFSeG0\nJew4S1N7nqqqKpHQ5XK5SFEUSiQSAu8fi8XI5XKRw+GgdDotxj2/V0wIJo+NSCQiLG2TySSMKu5/\nLX0Er75isRiVlZUJQ6yoqIiy2Sx5PJ68SVg2rvivy+VSja/zqdQNBb67ADklfrVkfY9o9wXw/wF4\nVfr8d68fV6LZ7z4AYwBss0p9epEpWXn5yMIp7hs2bKBgMKh6UUpLS1WuAvlYtmItFguZzWbVS/qL\nX/xCkCzV1NTQypUraePGjSoXkNb6mioTU26nfKx230KkXryPHJh0uVyUSqXyFK0c6OUAq8xNPpXI\nwTuti0vbJrnOKl/PbDYXdHdx+3liBnITBCt5dpV4PB5qaGggRVGEu6m0tFRA++S+stls1NfXR3Pm\nzFElI70dYrPZBJ/PggULRC1Rl8sllKWiKFRdXU3/9E//RMXFxVRTU5NXQo8VndVqpXA4TG1tbap+\nveCCC1STtny/PHHJnEI2m00YFvw8eCWWTCaFQuQxw/z5brebysrKqLKyUvSty+Wi1atXk9vtpvr6\nemppaRGcNel0mmpra+kzn/kMdXd3CzoL5ryvqKgQ19XpdNTS0kKhUIhMJpMYC263m9LpNBUXF4tg\nON83TwxNTU20aNEiAiCS4YxGoxiL502pT6Hob0LO4k6//vkpAC8X2O//IafEA69//i6AcSAXoJX2\n+9Dr+7XMKvXCEolEqKWlhUwmE3V0dNDAwAC1tbUJd0pbWxs5nU6VMvL7/SpFAuT8fXLGYVlZGX32\ns59VWbJdXV2UTCbpoYceolWrVtHQ0BANDg5SU1OTeFEKWUks0yn0c+WSVpQ3CkKwtSb7Hrlwh/a6\nXC9U/v5sriDZMmKudu0Exe0pdK6zoXMYr5xOp8lqtVJZWVlePdZIJCImXJ5kAaiW+zU1NTRv3jyB\nwHi7x57RaKTq6mpqbm4WfcJlDYFcVquMNOKJ6c477xQl+FjpNTc304UXXij6uRCuPh6P5xHNcd+X\nl5dTW1sbmUwmMpvNAm3EZFx+v19l+LCyl8c9K/K2tjYx8bAbaWhoiIqLi4Wbpb+/n/x+P4VCIers\n7CSbzSbeuWg0WjCOw0XYte8voC71JxOdyYbABz/4QTHOSkpKxMrgbVPqAPTIBUy/Kn23FcCmAvt+\nCjllXf76558DOFZgv2tf32/hrFLPf6EaGxuFf5yt7xUrVkxZHGD+/Pk0NDSUB4HkY3mAAShIoBWL\nxWhgYIDWrFlTsOix/JIpiiKuUwiKqP2/kFJnX6JcD1LbB1MpZFb48qpEFu3kwzBOIGcNKYpC4XCY\nDAaDoAHgF8xsNlNVVZXKD6+tTVroPgG1MjKbzcLnKnOL8DkymQyVlZUJ63zt2rUUiUTECsrn81FX\nV5eoCftOlKaT7ysSidBFF10kJhjZ/cD3ks1mVZQGZrOZfD6favxUVFSQz+ejvr4+MU4KTUplZWV0\nzTXXEJBTyvL9er1eoTD5WWlXRjzBsBHAdAUmk4mWLl1KQM7FyJWZZDbIWCxGGzZsIIfDQRs3bqSN\nGzfSwMAArVy5kqLRKNXV1YnxXlVVJdwtcqnF1tZWMVkDb9BxsIstEAhQUVGRGPM8Ntg4qa6uJrvd\nnjc5vJ1K/S4Az+D1wOmsUn/7JJvNqga9VnEUFRWJF58VPFsCrKzvvPNOuvPOO2nJkiVUV1cnIvjA\nG1SlQI5E6fLLL6f+/n5KJBJ09dVXU0VFBQ0NDakU/0zcKmfLKJXdIHIRZm0N0encMMXFxVRUVCSC\njkBO4cooCfletZNLIeudK/Xw0pm/t9vtqslBq2im4s8B8rMJHQ4Htba2CiuclSajYmw2m6q/+aWu\nqqp6x8efTqej9evXEwBVPdCKigrS6/Ui5uJyuSgQCNDg4KAg1IpEImS1Wqm1tVVVJIOVlXwN/j8a\njZLZbKZMJkOBQEA1AZ8tu9jpdFIgECCLxUL19fVCUbe2tpLX61X5wh0OB4VCISoqKhKMmz09PVRW\nVkbV1dV08cUX553faDRSMBgUNL1f+cpXqKOjg/x+P9lsNqqsrKRoNJpXsYrjTEVFRapSiLI7ju8r\nnU5TNBoln89XEOH2tih1AFchF9TUwhnPxf1yBrPuF5WwtcE82TwYtPvJRY0bGhpo1apVBLyxnLRY\nLCor0GAwUH19PdXX15PZbKbGxkZqamqi4uJilbU+f/58uvHGGymRSNCKFSsoFoupUutlCJmMMNEq\nXvmlm8qvzP9P55OXffryxAOoJwSZElVGHzAfe6HSe3hdCckvk2x9y5alXEhEi27gdk+FlpnKmuZA\nMn9ubm6mxYsXq47p7e0VLIyrVq2iioqKs8YD3i7p6OigOXPmUGlpqbB4eUywAuP7iUajlMlkKBwO\ni4nr0ksvFYFpZqEsRG7GClfuN7fbrUIHcdJcNBoVFrfD4VAVB4lGoxSJRCgYDNKKFStUzzaVSqlc\neHq9XjXx33DDDdTc3EwbN26kn/zkJ6oxyG1nK9vv91NNTQ3deuutYkLm/uHnJa+km5qaRN1Yfkdt\nNhvZbDZBPRGNRikej6uqjcnv33lX6gAuQw5XXlTgt/sBjCI/UPojAHulz7cip7wTmv3ue/34/3OB\n0t7eXqGc5syZoyoxl0gkyOVykd/vL1gSy2w2k9PpJIPBQKFQiDKZjAoD3dLSIqzAr33ta3kwKq3c\ndttt4gUrVDhXKwxp1LZpOt+yz+c7K9Uo35eM4eZBzv/r9XoyGo0q9Ae7OXgfzujj/bUUw4DatcPt\ncrvdQlH5fL48y162NIPBoPCx22w2qqioEC+l1WrNw9d3dHSo4heRSIT8fj+ZTCaBsGD8Np/nnS4e\nzZLNZqm/v59SqRRZLBZqb28XK0G2uKuqqsjn81E6naaamhr60Ic+JNwwgUCAYrEYrVq1ShggHo+H\nGhsbVUildDo9ZcUrnU4nVjter5fi8Tg5nU6R2RkMBikYDFIoFKJgMKhayWnZNBOJBAUCAUF7C+Qm\nGLmYeVdXFw0ODlJPT484Nx/PKzRFUai9vV28T4FAgObMmaOarJgjxu/3U2lpKZWUlND73/9+ymaz\neYyUcsB25cqVdP3114vzxuNxsRI9r0odwKXQKHQASwC87/X/GdI4R/rdBOAwgPuk77LIBViv0Jx/\nM4AfTXHtd2VAvxPi9/vzludcNKHQ/iaTiSorKykYDFJ9fb1QquxykAODjPo427KVxefz0T/+4z/S\nrbfeSsFgkD796U8TkFN0XClJ3n86F8tUVup0FWT4f7nN2mtoecz5OMYU8/dc5GDNmjV5beGycnKy\nSkNDg/j9Yx/7GClKrmAFUJjC12Kx5NEDaFdWLS0teRNjS0uLeN6JRIK6urqooaFBTER2u52ampqo\nsrJSBPA6Ozun7Le3QxRFyUMnmUwmGhwcJJfLRR6PR1DVut1uqqurI7/fL8oWcoBatoC1wpMiW9s8\nbrWkXnK/6nQ6ymQyVFNTIyZnDjaXlZWRwWCguro6ARd0u93k8/lUEyhfl59DLBYjm81GZrNZvEMl\nJSVCOd9777107733iglJDup2d3dTQ0MDeTweVSwoFAqJFbPJZCKLxUKDg4NUU1ND6XRa5VKSx1N3\nd7eojuT3+1XIIe6f86bUAVwC4DSADyOn3Fm+CuDj0n6cfMRJSncD2AcgrDnfP0GdfHQVcslHdf/X\nlLo8gLlqjDaxiC1W2YLnQcdLN/4+lUqp4G9ArnIMw6Sqq6spHo9TKpWi++67jz760Y+S2+1WDdav\nf/3rtGzZMrrtttuou7ubUqmUSBA5231MFSzUKtaWlhahFAsV2SgvL6eOjg7q6OgQVorsLmLscaHr\nyjC2rq4uVWKUVhHzsbILha1jVqRTcbAX4nKxWq3U3t5O7e3tZDabVYgQbeapXBSZl9+8qpILTRcq\n7vF2Cmd98meDwUA33nijatJcvnw5WSwWETC8+uqrqaqqijo6OlSTYFdXF61Zs0a4GTo7O4XS5f67\n5557qLu7m9asWUPxeJxcLhfp9XoqKipS+aftdrtol2zpcjWqkpIS0UZWshwf4fEdDAb+Wm6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wcOYGJiAqOjo3j66afF8Xq9HmfOnIFOp0MkEsGhQ4cQj8dhtVqxadOms/bT270pioIvfOEL+MlP\nfoKDBw9i/fr1AIAXX3wR3/rWtxAIBPDRj34Uzz33HJYvX47Vq1fD6XQikUjA7XZj586d2LVrF+64\n4w4kk0n88pe/xHe/+11RCi6TyeBPf/oTgJyLDMgFvUOhEPbv34/+/n7s378fzz//POx2O44fP46S\nkhKYTCbY7XYcPHgQw8PDCAaDOHnyJA4ePIjx8XFYrVY4HA54PB5s27YNDocDABCLxbBnzx4MDw9D\nURTMnz8fTz75JE6ePAlFUdDf34+9e/fiz3/+MyoqKhAMBvHEE08glUrB6XTixRdfhN/vh9frxYED\nB3D06FFEo1EAwK5du2A0GjE+Po6SkhJMTEzg6NGjOHHiBLxeL44ePQoiEmN2YmICe/bsES46j8eD\nw4cPw2g0or6+Hn/84x8xOTkp3CqhUEi4Ar1er3Bl2mw27N69G0DOpUQzDJTOKvXzvFmtVuE7PHr0\nKE6ePImKigp4vV7YbDbY7Xb84Ac/QG1tLTweD5555hmheF9++WVUVlbixRdfRDweRyAQwLZt2xAM\nBrFjxw4AgNPpRDQaRTabxU9/+lP09PQIhUVECIfDcLvd2LJli6pdrLwHBgbw+OOPY2JioiDChX3C\njIjxer34y1/+ojpHoW0maBmdTidQFGfbuD4kAFHT8uDBg7Db7YhGo5icnERzczOuvfZaNDU1ib45\nceKEQMZwe4LBIBRFgc/nw+HDh+HxeAAA27ZtQyqVgsViQSwWw6ZNm0Q9U75XRtAsXrwYP/7xj0Wb\nampqBNrC6/WirKwMhw8fFnU35X7JZDICVfRe2HiyKi8vRyQSwdjYmIjB1NbW4pJLLsGmTZvwve99\nDy6XC6+88go+8IEPYO7cufjABz6A3bt3o6KiAqlUCj//+c+FD3zdunV45JFHMDExgX379iEajeK1\n114T1z116hSCwSAmJydx6NAh1NfXY8eOHZicnFQ9t7KyMuzYsQMOhwONjY3Ys2cPtm/fDrfbjZMn\nTyKbzeKll15CNBoVdULb29uxefNmGAwGDA8Pw+VywefzYe/evXC5XBgdHcXIyAjKyspgsVjgdDrx\n2GOPCdTS1q1b0dPTg6NHj8JsNqO4uFiMk9/97ncAcsgXvV6Pffv2we/34+WXX8bo6Cj8fj+cTifO\nnDkj3lOz2Qyj0QibzYZjx47BYDCgrKwMzz//fN7z4Nqm3P979uzB+Pg4uru78dvf/hZutxuvvPLK\njJX6u+5e+d/ofunv71clsiSTSbryyiuFz/Gqq64SCRCQlqe8dGU3xNy5cykSidD9998v8LGFSseZ\nzWYVc6CMi+UsRf58++23C6KhQjVEC2WOtrW1TZnsw3K+kmYKZX2yMClUOp0WS9lLLrlEhTPn5TLf\nr7a/ZD+sts3f//73qb+/XyzruT/LyspUBGDMOxMKhaivr09wkmQyGZW/nqvv8POXmRbf7iSjQiLH\nZ1wuF91+++2i79gVEAqFKBQK0TXXXEPBYJCsVit1d3dTJpOh+vp6Wr58OblcLlEd6MYbb1SNieXL\nl9OyZcsEf4nT6RS85FarlVasWEGDg4NksVhEohG/J9zfXq+X7HY7lZeXk91up/r6empra6N0Oq3K\nj5BdIFqXIicNhUIh4Qtn7DpntA4MDAh3CwCRIMXxjWg0StFoNK9aWEtLCymKQhaLRXXsVARyAPJo\nsEtLS6m1tVUVz2hubqZEIiFcn+l0mhRFOWc+9Vn0y+w2u81us9v/pu3dtsT/t1jqiqLQ+vXraWho\niPr6+qi3t5c+/vGPi5mcg4pcCsxkMonU46VLl9LSpUsFNWc8HqfGxkbB9zw4ODglB0mhtnAhBa1V\nGgqFRPCFMcfT3Y/2/KFQaEo89bkGTbXogal+46zD4uJiWrRokag4z4RJXq+Xvve97wlLja1GzoSE\nZMUlEom8c8vXTSQS5PF4VBmK3O/yd4Cadpj7lHMB+HdFUai2tlbQ1MpUrO9koYtCkkgkyGw20x13\n3CEqXfFYrayspHXr1qnyCYqKikiv14t7+Nu//VtqaWkRdADa/mxsbKRPfepTlE6nVRQBzL3S3t4u\nLGjOAnY6naQoCnm9XpHdGY1GKRgMktPppNWrV9NHPvIRkRUK5Aph1NXV0eWXX056vV5kvnIBjAsu\nuEDFuilb3IxcYr58u91O6XS6YACzvr6ePve5z5HFYiGfzyeC7UDOojabzRQOhykSiVB3d7d4V5xO\nJw0MDIj74vPKXEaBQIDC4bCw1G02myCek9swU52pv+uuu/Be3u6+++673u02FNq8Xi/OnDmDyclJ\nGAwGTE5O4uTJk7DZbCIb1OFw4NFHHwUA4V/bunUrfD6fwE3v3r0bW7duxdatWzE5OSlwwWNjY6ir\nqwMA/OY3vxF477NtiqKgpKRE+MF5IyJ86EMfwquvvorh4WERjAmHw5g7dy7+8pe/wG63Ix6PC8wu\nn4+3kydPwmg0FvSJy1jtmbRR9r8X8sV7PB5YLBZMTExgfHwcJ06cgN/vFxmNOp0OBw8eRElJCZ5/\n/nno9XocPXpUBNoY58uxBgA4fvw4FEWBw+GA2WxGPB5HNpvFnj170NXVhc2bN2NychI7duzAxRdf\njJdeeknEHnbu3Cme4djYGIgIFRUVKCoqwunTp/GhD30IOp0Ox44dE9mnAJBKpTA5OYnDhw+jrKwM\n+/fvV7Xpnd6MRiOMRiOKioqwb98+bN68GX/5y19w6tQpnDhxQmT9Pvvss5g7dy727duHkZERDA8P\nQ6fToaqqCm63G7t374aiKLjuuuvwpz/9CcePH8fY2JgYL/v27YPT6RSBPr1ej4GBAWzatAnHjh1D\ndXU1DAYDTp06hZGREdhsNpw8eVIEs00mE06cOAGDwYBUKoX9+/cLYMGDDz6I9vZ2JBIJbNmyBUeO\nHAEAnDhxAsPDwzhw4ABaWlqwfft28azKyspw+vRpjIyMwGAwYHR0FLFYDEePHsXY2BjOnDkDk8mE\ngwcPYmRkBA6HQzXO169fjy9/+csYHh7G6dOnceTIEQwPDyObzWLr1q2YmJgQY/T06dPYtWuXCMi/\n8sorIt5jMBgwMTGB48ePi3NzAHbHjh2wWCw4fPiwyGg9evQoWlpasHfvXtx11113z+ghv9uW+P9U\nS13LI240GgWelLPQmIva5/PRRRddREuWLKFVq1ZRW1ubqgJ8JpOhTCZDOp2OGhoaRDZed3e3yHSb\nzrIrhBfX8ng3NDRQdXU1mc1mVXX1QrzpbLnF4/GCPvapKhLJbZiKB/3N+pL1ej01NzfTpZdeSuFw\nmC6//HJyu91UWVkpLK6WlhYqKSkR9+ZwOPJWOAwx5HtgkjOtyHTDvOIBoHpusrS2tpLNZqPly5fT\n8uXLyWg0UmVlJYXDYaqoqKBoNEoej+dd8aVrxel00t///d+LZxkMBmnevHk0b968glwwbrdbZF72\n9fVRfX099fT00Pbt2wXXicxYyMcx1006nRYrleXLl4vnxZYsv0sMXeU4SHV1NYXDYert7aVUKkV+\nv58ikQiVlJRQKpWilpYWuvDCC+nCCy+kW2+9lYBcoXQgtxK1WCy0dOlSqq2tFaUJgdwqji1lo9Eo\nagCUl5eLLOBgMKjK9C70XnF7edxzzEteAct6wu1207x58wo+k0AgQM3NzYI/3u/3U0lJCdXX1ws4\n5ox15ruttP+nKHXGrG7cuFGUx+Lfbr75ZpECz8kYjEW++uqradWqVaqXhQeG1+ulm266SXApy8kL\ncqB13bp10yanFHJ9rF69WiRVBAIBCgaDFIlERIVzDtrORBHLv3G6v4y1fjN49TdTgLqiooLS6TQl\nk0kyGo2iRBiz5nFaeGVlZV6NUH6Bte2Va0lq74eVAP/Oz5xxxrw/B7uefPJJuuiii+iiiy6i6upq\nam1tpXQ6TfF4nBYuXEihUOhdd7uUl5dTe3u7cAPw+OAAb1lZmWps83i+5pprKBwO04MPPkgNDQ30\n4Q9/mDwej8CaL168WOD+HQ4H1dXVUWlpKSWTSeECdLvdVFZWRg6HQxwXjUZVwXEmZeNyeNzP7BqK\nRCLk9Xqpurpa1ZcrV66kwcFBstlstGDBAorH4yJo7nK5qKamRlQVstlsguJX5u9nJV1ZWSnqg/p8\nPkqlUmISuOWWW2jjxo0E5AAExcXFNDQ0RJFIJK+WLRsUjG3nz6WlpdO6H1mqq6vpqquuotWrVxMw\nq9TPu7S0tFBLS0se6f6CBQvO+qIuX76c2traBFIim81SMBgUkXxmf9Pr9SrLYMWKFVRcXCyUUSEO\nb3lwaP3dBoNB8JLL52Xf6FSFq4HcRMIUqdprnku/TTVgC0khZI18vaqqKpHt5/f7SafTUXFxMen1\nelHQubu7m0pLS/PubeHChQXbzv1SXV0tMv7Yj1/oucrfMYKD2+NwOOiTn/wkffKTnySdTkcrV66k\nZDIp+E60RbDfaVEUhfr6+shms4lEG0DNP+TxeKipqYlisRi1traSw+Ggm266iQDQXXfdRZdeeilZ\nrVYKBAK0atUqMpvN1N7eLrIs29vbyefzUU1NDVVUVNDGjRsFd0wkEqE77rhDJNZ5vV6BvpEZD1nh\ny4l2sViMysvLyeVyUVVVFS1cuFBwvLS2tgoWyiVLllB5eTklEgnhN29ra6PKykpyu90COaUoSh5/\n+pw5c6impoaSySRFIhGxwuDVRCAQoC9/+cs0NDRE3/jGNwjIKWj5HioqKvIqG8ljR7uC5u+Z991s\nNlM6nSabzUZVVVVUXFwsVkGzSv08yuDgoPjfYDDQ0qVL6f3vfz95vV7R4Qz/Wrp0qagvyQMFyE0A\nnLrMLzdTdTKMjBVgNptVKWEmSJrOIuZUaPk7mX6Wl5kzvWe2jBoaGvLqiRaybKc715uhlNWm8ut0\nOgqHwyqyLu4j3o9XNn6/X1xT2ycARH+z66nQ/Xg8noL9JUMhZdeOxWKhaDRKK1eupJUrV6qyYEOh\n0Dn1/dspCxYsoHnz5gmKWqPRqBrfzOn//e9/X3wXi8Woo6ODbr/9dnHvPD7C4bDIjB4cHBSuvXA4\nTCaTia666iq67bbb6LbbbqO+vj7yeDwCzvv1r39dkF9xMFwe88yLLovH46GlS5dSJpOhpqYmUaOU\nJ57KykrasGGDyEbl+gKlpaX0D//wD+RwOKiiokLF5e/1egUdRHd3N4XDYaqurhaZ3FVVVVReXi5I\n826++WYCcqtxrfEgv7dWq5WSySRZrdY8N47WYOCCN5lMhgwGAzU1NYlgO68SZqozZyGNZ9nmzJmD\nl156SSTlbNy4ET/96U/xhz/8AceOHRMZawcOHMAtt9yCH/3oR9iyZQvKysrQ1taG3/zmNwByGaaH\nDx+Goigie+zgwYM4ceIE2tra0NbWhomJCRHkGxkZwb333gsAGB4exvDwsHhoTBwE5JKdeDty5IhI\n8LHb7fD5fCIwNj4+rspGPdt26NAh6PV6vPrqqyLgYzAY5MlWbERqwi/tJifedHV1FdxHPr7QuSYn\nJ/Hqq6/C7XajoaEBdrtdBLImJiZgMplw+vRpWCwWjI+Pw2g0AnijT+Rkpn379mHfvn2C0le+H51O\nB51OJwjU5I2TdnQ6Hex2u6DZ5eDxqVOnYDAYRD85nU6RrHIuff92bR6PB5s2bcLTTz8Ni8WCU6dO\nYe7cuXjsscewcOFCLFy4EK2trWhubsbatWvFc9i9ezfa29sRDAaRyWRgtVqxc+dONDc3w+v14vHH\nH0dXVxdeeeUV1NbWintNp9P4z//8TzzyyCN45JFHsGPHDhGsTiQS+OEPf4jDhw9j7dq10Ov1eO21\n15BKpaDT6TA+Po4XX3wRtbW1AHJjorOzE9FoFE899RSICOPj43C5XHC5XHjwwQfR3NyM48eP47HH\nHkM4HEZ3dzcOHDgARVEwNjaG2267DQ6HA1arFQaDQZC3nThxAkSEn/zkJ7jwwgsxPj4u7q+5uRl+\nvx+KosDpdKKurg6//vWvodPpsGXLFrz66quqPh4ZGRFj7/Tp/5+97w6Ps7rSf3G9i1EAACAASURB\nVKd907umaTSjUZnRqGvUre4m2djINjY2LjGdUBZDCJAsZH8JIdmEbPLAk2wSAtnsZknCJk9CgCwt\nBEjBFVNsbNyw5Ya7bPUund8fyrl8MxrJMoElEN/nuY9GM1+53733O/fcc97znn4cPHhQOGidTidU\nKpUgjmOZolKpEAwG0dPTg3379kGj0Qhq5sLCQkEBPN1yMaJ0iuJyudDc3IwTJ07g9OnTAIBAIACF\nQoEDBw6gvLwcR44cQXd3N3bv3i0Y5HJycjAyMoL9+/eLyMSqqirs3r0bg4ODsFqtInJN7gWXF45k\njEQiyM/Px65duwSPMxFBrVZDkiQhSBK51dPS0nD69Gnxvd1ux5kzZwC8L8TkKBT+zH91Oh2sVitO\nnjw5Aa2i0+nikAHyc+XX/zCKUqmEwWBAT08PlEol8vPzYbFYsHnzZmi12rgFR6/XC6Y+h8OBUCiE\nAwcOoKOjIym9wcyZM/Haa68JJBNHP3L7/X4/2tvbJ42ALSsrw+uvv45QKIRjx47BYDAI5suqqips\n3rxZoEn+Xsrq1avx3HPP4ezZs6isrMSWLVsE/zgXm80mnqO+vh5jY2OIRCI4ceIEjEYjTCYT3nnn\nHQDjC+SZM2cwf/58rF+/XkTshkIh7NmzB5FIRCyOp06dQm9vL4LBIJxOp8gTwBQNLpdLRBwrFAq4\n3W4cOHBACPDU1FShFMViMezduxf19fUAxqM9t2zZgoMHD+LSSy/F+vXrcfLkSbz33nsIBAIwGAx4\n9913ccstt+AnP/kJJEnCyMgIuru7YTKZBDrG4XDg3XffjesPAPD5fDh79iyi0SjWrl2LBx54AKdO\nnRLh/GNjY0k59nkutba24ne/+x3S0tIwMjKC06dPC+HPfX78+HGYTCb09fUhIyNDtI8VBroYUfrh\n1T/84Q/061//mn79618Ltrnrr7+edDodff7znyev1ytsa2q1WuQEVSqVpNVqadmyZWLb+vDDD5Pd\nbhe80QqFIs68MlU7mAyLj5OjCOQZhQoKCgSumL9LRDWwGUWOY5ebVthcoNPp4q4jb4P8eHm0pfz/\nxCTGic+UzE8wVdSq2+2m9PT0OOeaHPNbWloqkAicNFuSpAm44/NVebQvMG7vT0Q8ZWRkkCRJAjdd\nUlJCa9eupbVr1wrb/FSxAB9XZcfb1VdfTVqtltauXSts6pyjlPm9i4uLKRAI0OrVq6m5uVn08ZIl\nSwTnN9uoKysrKS0tjfR6vcgoFQqFhM8o0bGq0WgEZz/fn+cIZ7QqKioSzleXy0UpKSkUi8Wourqa\n0tPTBRFZIBCgRx55hAAIJAzne1Wr1TRnzhzKy8ujcDhMGo2GTCZTXHQqm1FNJhPpdDrKysoSfqeU\nlJQ4/n5GQMmRY5PNL7PZTPX19eT3+4U5yWKxkNvtplgsJvKR8hwD3o8o5yhUjjC9aFP/AJXDqDmv\nIk8wh8NBN954I9144430la98he6++24RJs7nZmdnU15e3oQgGBYOTIsrZwW8ENs0/8a2UL5Ofn4+\neb1eKisro4ceeigupRgQ72ySO+rk95oK9cKpyuSCPZFuVn6OfPGQJIkUinE6XJfLNWEBmKwtyRjw\ngPEFQm5Tl/elXOAaDAbxTEzrKkfvJDJd8qKWlpZGZrNZvEwajYbmz58vGCk5GYLc96HVasntdovn\n/tKXvkRf+tKXSKfTCYrdv5eqVCrJYDBQeno6Wa1Wuu666yYcw/OHw/PT09MF2oTngUKhIIvFQhs2\nbKBYLEYrV66kxsZGqqurEwqK1+ul7OxsKisro9mzZwu7fUpKioD8yhdwhUIhxlOv1wvHKI8zO2QL\nCgqopKSElEplHOPn3Llz6a677qI///nP1NraSsC4QLVardTc3EwlJSWCvtdut1NmZiaZTCYKhUI0\nY8YMIUgzMjIoNzdXOH89Hg/dcMMNpNfrhX2eaTmKiopIkiTSaDTk9XrpoYcemrDwcxKSjIwMSktL\nE3OTYbdcE+f8v/zLv0y41kWhfoE1LS2N/vmf/5muuOIKKi8vJ5VKJbC8iULI4XBQKBSiG2+8kVQq\nlVjF586dSwqFYgLiQ559B8AEjm7OxDOdl5LbKhd0/FnOS83tlmvTNpttAjQy2ULCWjBzkttsNrLb\n7XEcHfJrJ+LQeRcy2X3kfXQ+DLvFYhGaES+k8uPkkZAsdJJ9TibMk1Ve+KqrqwVe2ul0ks1mExpV\nOBymmpoacjgcQoO/7LLL6JJLLqHMzEzKzMwkIvrIsxl9kMoOzIaGBiopKZnQ51/+8pfp1ltvpZKS\nEpo7dy45nU666667yO12U1paWlyfzpo1S+xStFotpaenk0KhoKKiIpGzE3gfNjlr1ixSKpU0Y8aM\nOL6egoICcjgcVFdXJyC3fr+fMjIyqL6+nrxer8BtswP62muvpVmzZlFzczM1NzeL/4mIFi5cKDI1\n5ebmUn5+PtXX15PFYhEJrA0GA+Xm5pJaraYFCxYQMI5SA95Pes67B94lMFSTaX9dLhdlZmZSaWkp\n2e12mjdvHuXl5Ylk2vJ+5QXojjvuoEgkQlarVUTDJs7JQCAgeGXkMMmLQv0CK4ehZ2dn07e//W3S\n6/VC85AkSRBjWSwWCgaDZDQaBeaVhYZGoxFE/PLkEnwPFuyMemEByV52/n0qhMtkdAGRSGTSrOjJ\nhFYyYQwgLpH1nDlzaM2aNSRJkkgOrVQqk0Lz5IRFyZIFABODlibTyJNVThoif0Z5KDX/TeR5n87u\nR/4/mwP4Oxbser0+LnAkGAwKcwQwjq5g+JvZbKaKioq/S6GuVCqpurqaXnzxRTFWK1eupKuuuoqu\nuuoqyszMFOaqpqYmWrduHf3Hf/wHZWdn09y5c8lqtVI0Go2LoQDieeYdDocIdeexY/TXvHnzxLlu\nt1vMFTZDcpuysrLojjvuoGAwSD6fT5jempubBa+5VqsVkF0Ollu6dGncfGP0SVpaGpWWlpLf7ye7\n3U4Gg4G0Wm0cpzvvLCORCJlMprggNYavOhwOQSfBxwYCAVIoxpNZcMBZVVWVQLsB4zzpy5cvJ6VS\nSdFolGpqaibwtQPvm3GysrLIbreLoCjgolCfdi0tLaVoNCo6rqGhQdgci4uLaeXKlXErqVyosmYi\n15ydTmfSQCEWDufTFKeD604mqM6HgWYBmozlUX5MOBymmTNnkkqlIrfbHYfFnkwIyxcEhWKcY4a1\nnvPVyZJNyAUzvxwsMBlfLccD8+IqhxzK/57PX8FVvqgxm5/b7SatVktarVZkmfd6vdTS0iKyyhcV\nFYnsPxzY9fdcFyxYQJWVlaTRaCgcDsf1Efel0Wik0tJSuvfee+N8GAzjW7JkCRUUFFBra6vQoHnH\nycLa5XIJ2zGbOLRaLen1epGtiIOBAND/+3//T4z1mjVrqKmpibRaLTkcDmH+Ki0tFVhyxqkz0+ni\nxYsJGI8IDgQCIiCN567ZbBa8QfyscjMHt4NNMoznr6+vF6Ypfo8cDgcZjUbKy8ujWCwmWBoLCwtJ\no9EIHD+/c//1X/9FsViM5s2bR1VVVaJfEscmJyeHrFYreTwecrlcYqd6UahPUXNzc4UzraqqisrK\nyui6666jgoICuuuuuwROlI/n7RZXtrfX1NSQxWIhpVJJP/7xj8U1eUve0NBA0WiU7Ha7GNhkWuCF\n1mS0sZM55BIFGpNcJRNyvHvIyckR1Kl87FSBSsk0fjml6t9SdTodOZ3OpHjz8/WR/P/i4mK69NJL\n6eabb6Z169bRunXrKBAITFiAOTGx4q9YdflYRSIRKikpEbbVAwcOUFpaGuXl5VEkEiGj0SjoWj+K\nefth1euvv57MZrNwFF5++eVCuPL4A+P29csuu4wACOe/vNbX15PZbCafz0d2u10IxIaGBnK73cIM\nxwRZXq+Xli5dKsLxU1NTRbYgYFzA1tXViWTNwPgOiAWz0+kUgVMej4fC4TAVFBSIICK5WdNgMJDJ\nZKJ7772XQqGQwMHLYxui0ShpNBpKTU0VGj3P39TUVNEn7BDn4Cw5PUBKSorQ2j0eD0WjUQoEAlRf\nXy+ydimVSuGIZcexPIbEaDSKvs/Ly6OMjAzyer0UCATi5v1FoT5FlUeyXXLJJeTz+aiuro40Gg1l\nZWWRzWYjv99PCxcupFtuuSUOoTLZNcvKysQ1NRoNNTU1CQHKNVGQsuklmW068Rw56+J0tE75sedz\nyDocDsE7IXcyAuOOI/nxk3n5z2cbn85vk/3Ojin+X6PRCNtrYqo7rrwN9vl8VFhYSDqdboLfoqSk\nhB588EF67LHH6IYbbhCZ4hPHOSMjQzi2VqxYQTabjXbs2EGNjY2k0WimvSv5e6k8xnKEDwd7rVy5\nUgjJhoYGsVNhDZgjqAsKCoQGyddhwVRYWEhKpZIkSRLp3AwGA/n9fkpNTaU1a9YQML5LMxqNgr2Q\ng234MzBu3/b7/aTRaITT3u12UyAQEBGi2dnZFAwG40yAWq2W/H4/paenCxNHWlqaSJnHKfh4/vPi\nwefLo01dLhepVCqxM9fr9bRs2TL63Oc+R2q1mgoKCkREsV6vJ5fLJYARyarFYpkQ0Od2u8nr9ZLH\n46Hi4mLKy8ubEPF6UahPUf1+v9DI5E42Hnwe+G984xuUnZ1NV155pThm1apVlJubOyHXppzoqaio\nSPCBnE+ITZUUYrI6WZIH+SRJ9h1/b7VaSa/Xx0EBY7EYXXPNNRMEGtuo5d9Nlwa4qKgoziwiRwax\nc0r+TPz5M5/5zIR78fOyc1K+YEqSJEweiRp6ImEZQw2TtTclJYXuvvtuAt63/ydq8tXV1cJxt2PH\nDrrmmmvIYDAISuVPSlX+NXn5vffeG/c9J55mQc3zIRaLkSRJQkMOhUJxPgNO+F1SUiKIvHgRjUaj\ngitIr9eLKFJerBnyx9QMa9euJb/fH2eKZPNiJBIRwj3RHl1cXBynBDG5FgvltLQ0QdlQVlYmok55\n7OXX8ng8tGDBAlqwYAGlp6cL8xswbrpqbm4mo9FI+fn5Ilo7EAiQ1+sV9LnTyWPLlU054XCYotEo\nWa3WuAQawEWhPq3KGX1aW1vjwp39fj/NmDGDYrEYGQwGKi8vp4aGhgmc2vJB420Sczrz91Pho/nF\nKi4upuLi4gnHToWI+SD24sQqt5HLzU2ccJjb+EHt/Ml+T8YCyDzkZWVlSaGYrMHx+XKzTjLbOx8n\nSZJABCVbPOV9qNVqhWBesGABPfvsswLOmJWVJQik6uvrqbW1lYiIvvnNbwpB91HO04+qbt26lfLy\n8ujKK68UTkGe4zz+PPZarVaMQ1ZWluBIYQGr0WiourqaioqKKBgM0tKlSwXhGt9v/vz5gmxNLlCB\ncTu9w+Egu90eNxfZrGg2m8V7xcI8EokIH0ZeXh498sgjwgRjNBoFZzxztfN1FAqFUMoYA872cF5o\n8vLyhPLm8XjIYrGQ1+uljIyMON4mt9stfE+8YDCP0FR9n0gbwSiiiooKysrKiksmz/WiUE+oiQLT\nbrdTOBwmp9NJeXl5wu7t9/spJyeHbDYb1dTUUHNz8wRBJOeNSFYnc4YmwgCTacBsa7sQNr/pmj74\nmpx6CxgXpMlsy4wv54klx3mf73mmS+JlNBqn3G0kMxvJ+yURsqhSqUR2+GQvznT60G63i3uUl5eT\nyWSi2tpaKiwspO9+97vU0tIihMu9995LxcXFHzvz4t9SOUFDY2Oj4CnihTARIss282g0StXV1cK3\nAIwHNDHUNzMzk4xGI7nd7rj3Tq/Xk8/nEzBUg8EQJ6DZLBIMBmn16tVUXV0t3gfeHTE5Fy8mnCpP\njvvOysoSCkt2djbp9XqKRqOiPWq1Wry/ubm5QkkoKSkR6e/kc4cDlSRJouzsbPJ6vaRWqwUKxmKx\nUCAQENfJy8sTplh+z3i3kGwMuK2xWExg4v1+/4T5e1GoJ6lFRUX09a9/nYqKimj+/Pmk0WjIarXS\nrFmzxIDY7Xbyer1CewPGtYiWlhZqaWkRbHMsCNjZKr+P3KQjFxoXolXL81lqNJopnY68bT3fdi+R\nJW7NmjX0l7/8JQ7mmHiO/Jpyut3Jnm+63ye7frI6FapHDgFlwSrvJ6ZDlj9bMgHMbTSbzaTT6USb\nUlNT43YBl19+OTU2NtI3vvENUiqVdN99931oc/PjqDabTWSPYo0TGLc9r1ixgoD3g894nvHn73//\n+wRAIKWAcVOX/H+dTkcpKSnCH8U7U97V5uTkiDnFSoXRaKSZM2dSQ0MDZWdn05o1a6i4uJgkSRJa\ne2NjIykUCqqoqBC01fKIbPmc4UXD6/WSyWQim80Wh5GXV24DO0bz8/MpPz+fYrEY5efnU3Z2tsCW\n8yLCuHWey0wxbDab46h32QyYmP2K/VgpKSnCwV5RUTFBpgAXhXrS+qtf/UokCAbGt+TsuU40D7DW\nnngNxrLy/7zdkztpeACThd9Pp/Kx11xzTdLfJ8OrT8ZsJ2870/vabDYqKyubsh1y/nG+7/mcoMm0\na3ZsTvacU1W53V/+HPz8/KLL7z2Zz4HHk49NJuCTaVMGg0FohHV1deIYIopjOPykVaPRSDNmzBBj\nrdFoqLm5WfTtQw89JNAbPA6spaanp1NeXp7oYxZyPN48NpmZmcIezc5E+fxikyebRzjoyO/3i6hU\nYHxRVavVZDab6eqrr6avf/3rlJqaSpWVlXE7CqVSSS0tLYI1kxUzRq14vd6kJlGFQiFoDSwWC+Xk\n5Ah7PEeKl5WVCd8NB+YB44og0wtYrVbBl859o9frqbm5WSgcPp+PjEajoDgA3o/SZmRPIsjir/Pt\nolBPrB6PR+BCFQoFNTY2Um5urrDvmc1mikajcROPscocQAGMR44uXbo0Tig4nU7SarVxdtrzbcun\nEmoqlYokSaLq6mqaMWOGWIgSo1MTr8W2Sf6et7O8zZQkSQQ7KZXKuAleXV1NwPvas1qtpuzsbFKr\n1RdsypiOSehCYYqTVR4Xvm/iwssve7J2ns+sJE8owTTJwDhipLW1ldLT06m+vv4DObw/7lpeXk42\nmy0OXif3SzDskZ9txYoVpNVqyWg0CiHOcQw2m43uvPNOuummm4Q2WlZWRmq1Os5RmkiTYbPZaOnS\npSRJEpWWlsbBEsvKyshkMomAIqvVKnawx44di0M+yf1YKSkpVF5eTnPnzhV8ND6fTyDNmGs9UdHg\nSNb8/Hxyu9108803080330z9/f20dOlSYfMvKiqK2xEyZ47dbheLE89tnldyAEKiydLpdIp5pVAo\nJo0HuSjUZbW2tpYWLlwoBpyxoiqVimbMmEFqtZq8Xi8tW7aMvvjFL9KyZctozZo1ccmL5QPPW9Jk\nJpELEeoXUrOysmjp0qV00003TXoM31utVtPixYtp1apVcfhj/l2r1dKsWbPiYGJcJxNyiYRjF/Js\n0zn2g16bXyoeG37+6V5HrtEnWwy4yk1qOTk5VFFRIbbx06F4+HuuzMXCVb47UqvVcciuzMzMOE1c\nr9eTSqUijUZDd955J1VVVQlUTDgcJpPJJDR1Hh/uS4YYAuNmHMatWywWWrJkiVA8iouL6ZlnniFg\nfNd02223USQSodtuu02E9LOAZ1s3C1WlUinMGbyblmvDkykWOTk5gsdn06ZNlJmZSeXl5VRVVUX5\n+flJk13wzgR4P/E5m2TkSVd44eR+MZlMFAwGqba2dtJkLsBFoR5X586dS0A8EVXiNrukpGTS8HYg\nXvtkj3l+fj4Fg0GqqamJM9XIBXuy6yT7zBNwKu1dp9PRqlWrzvu8ya4j/87lctHKlSvJ4XBQdna2\n2AImQ6YA00uwcT5TyoUIPs4AcyG7g4ceekh8TmYzra2tnVawF++QEhE2cu2Jd3aMsPkw5ujHURct\nWiQSZbBNXavVJhV0CxcupFWrVomdK8PtJEmikpISoe1zPlaz2TzBEc5CuqGhIY7sjDHdGo2GAoGA\nuKbH40kKUlCr1SI2gM1G8oWchafL5RJze+nSpYIeQKVSCWWN7eQpKSkUDAYFJv7OO+8U5pEbbriB\n8vLyqKSkhEwmEy1btmyCQqdQKCgUClF6erpIyZesz9m5vGjRIiFTrFYrVVZW0kMPPTSlSXS6MvNi\nkoyL5WK5WC6WT1P5uDXxj1pT5zBnxqqyU0N+TF1dXVxgDNvdWWOUp5LjPJgrV64Uzhv8VcObPXt2\n3NZ1Mu01GYf4+RyQ8v8vueSSadtwp7q2PK0eY3QTj5FzZCR7DvmznI8WgJ1oarU6zuE0Vd/EYrFp\nE38lUiXITWDyayQ6VZNdS6/XU2NjYxyKQaFQxAVtyVENn+Sq1WrJ6/XGOSbZVKHX68UOtrS0VFAo\nMzSRtVt2uFZWVop5xERw7HBkbv68vDzhPPf5fHE2fYPBQLfffnucbZ+5YtjkYTQaKRQKxeUQmGy+\neb1ekiRJIF+CwWCcKYSfTT6OVqtVRJ1brVYKBoPC/5CdnS3s8kz8JW87MO6b4vkln3c8j3iXwLsj\nOZnfVAnmL5pfZJVtfHPnzhXMZ8mOk5tkMjIyRGSc1WqlsrIysTXiQIHCwkKxJUs8f7JJFggEBD8I\nm4XkQmY6TkVeqCZzmHJi6en0DTMPJvK/J6uJ9+OtL7c5GTlRYtuSfcfJRKZ6brlDl53Ficm0gfeF\nUTLfwFT9m1gdDgfpdDqRaIG/02g0lJubK+hd5ainT2JlTDbTP8diMTEvS0pKyGAwiMW/ublZCFu7\n3U6NjY1izCORCNXW1lJ1dXXc4s54dBZ4DodDEGOZTCZhA+ex4YTijY2N5PP5qKysjIxGo5jzLJAz\nMzPFApuamirecfn89fl8wpZvtVpJqVSS0+kUplJ28vJCxgpGTU0NZWRkUFZWFmVlZVFdXZ3IUypJ\nkshXCozj3CejD2G0GEebyoU6w6YVCoWgH2CaisnqRaGO8ZWRseRTOc1YoMkTX+h0OvrWt74VpzEA\nmMA1wpMlmdCYjgApLi4WyYqbm5snxdDyi8baMSMCJkOaMCnTdOCU8owzU2kK06nns4PzmEyXw4Yr\nh5fPnDlTaEvhcJjcbrfAl/OxTAXAzybvG7kNXD5usVgsTuuSty0SiQjt6tJLL6VAIEB33333BIje\nJ7Wy/4I1YqvVSuvWrSOPx0N+v5+ys7PFvOdEMuvWraN58+bR/PnzRbCez+cTCburqqpIkiSKRCKC\nV8br9VJ9fb1YqAsKCqi5uZnKy8vF9ZmdMS0tTSBRDAZD3HsoHxuO+pQjz+Tj6/f7BfGeQqEQiwvv\nDkpKSkilUlE4HKasrCwRZc6osWAwSHl5eZSXl0fZ2dmUkpJCBoOBnE4npaamCkKzxPkk98+ZTCbK\nyMggnU5H8+fPJ6VSSXa7XVDvXnHFFWInM9U4XRTqeF+7k6etklfWaqcS+GazmRwOB11xxRV0xRVX\nUEVFhfBoM2pGPqDTCQKarKpUKqqrqyOj0Uhz5syh9PR0ofW4XC5avHgxud1uca9wODxhMk8WcZns\nheAqb+8HEVKTLRzJHG5yDXq6KBfG18vDx9nBJF8cWHicr628U0q8f6LpjBMqAOOCvaGhgW6++WYC\nxp2l01kwPwl19erVdMkll9All1xC9fX1Ag+emppKTqeT9Ho9ud1uKi8vp9bWVtq7dy8BoJaWFsrN\nzaXa2lrBKtjS0iIUg3A4THl5eZSWlkZpaWlUUlJCBQUFlJmZKRJVMD9LMBgUgv/RRx+l1NTUuEhn\nZk1kwcwp7vR6vaDx5bEwGo1ksVgoGo0KB+itt95KwPsRtCyUc3JyqLS0VDhr6+vrKRwOU1FREdls\nNqG9X3fddUlNkHIUTKJQdrvdQkljpkhgXDEwmUyCNpiJzs6nUP3DC3UWhjabjf74xz/SFVdcQaWl\npSRJEgUCAUpLS4vTihlmlWw7LRdO4XBYbBcT7akfBMLICwtv1WbNmiWECxNvAe8L25aWForFYmQ0\nGgWuPNk1+S/TBct/n0yb5jDx87V3su+5rdNBylxIX021SMq1L3n72PabaFNPXGg44lCSJFq8eDFp\ntdo4IiWfzxdHHFVVVUWZmZnkcrmmjLD9pNWZM2fSzJkzBbpEo9FQeXk5+f1+YX654oorSKfTUWlp\nqcg5wGYE9lfV1taSxWKhlJQUMhqNItgvHA6T1+uNY7QMBAIUi8XIZrPFmdd++MMfktFoFGYa5jyX\nJ95QKMapbpmJM9E3M2PGDFKpVBSJRCgUClFJSQn5fD5KS0ujQCBARUVFgus9Pz+ftFothUIhwY6o\n0Whozpw5NGfOHHFt/svv/4XMYZfLJZBG8+bNEzuU8vJyqqiomFbMxj+8UJ8sirGkpIRmzpwpbMm8\nFZILD7kQ4QmbLDk029blwiRR4Mj/ns/kMBmfTKJ9fMmSJQSMC092FiWj2ZUHTU1FLMbPxZrwdCYr\nwzone/5ErebD1mjl0a3yv+yMlR/H/ccCYf78+XGsivK2GQwGQeAkD91Wq9WUl5dHRUVFInQ80TT3\nSa1so87MzKSMjAxB+WqxWASb4uWXX04qlYqKiopEzlLOSwDE01rYbDYh9OUUyHa7nVatWiXGp7Ky\nUgQmsXnL4/EISlzmWs/Ozo4jlmMN/Xvf+15cdiKukiTR97//fXI6nYJi1263k8fjEQF4oVBIwDeL\nioooLy9PcB3x8zOkMSsri5xOJ7lcLgFJTBbxeb4qt73PmjVLOGKnuzv+hxfqXNkJolarxQDyROZk\ntMxOl5eXlzRrDWuhHGiROAiJAmsyu3iyY5kGtKysbFpICqPRKIR6eXk5Pfzww+J55Pfg+3D06FQv\ntNynMJX5Qm76kSNNlEplUmdRS0vLhLYla+N0BU/i+fJFcqodBPC+XTwYDAona6JjiheqlJQU4cPg\na5hMJsHUx9+fzzH8SaxWq5VycnJEv4XDYWFycrvdpFAoqLKyUiSBkSSJCgoKhHmG+c0bGhrokUce\noZKSEqqvr6f6+npKTU2l8vLyuHnh8XjELorD+m02mzB9RSIRKioqEn3PoWSrwAAAIABJREFUyUo4\nR2giAkv+XuXm5lJ2drbIjcrIF447YIoH3u1xYo+KigqRko+VE4vFInKURqNRSktLI71eT2q1+oKS\nwahUKqJxwZY0nd1U9aJQl1UOdwfG7VmcUZx/LygomMCPLhcGAISzRK1WiywqiccyG9xUbVEoFEI4\nTrabmKympKQILYaTFvCOQ27/Y4GZ6EA1mUzkdDrJYrFMuoBMlopNHlGZDDqY+Jm1p2TCnrXp8wli\nALR27VohACY7JjEqdrIaCoXIZrNRIBCgQCBABQUF9M1vfpMWLFggIoXT09PJbDbT2rVrKRQKUUFB\ngfDJMMFXSkpKXGqzT0Nl4VhWVkY2m00IVLfbTSkpKcLxWVhYSOnp6RQIBOL63el0UigUorq6Oioq\nKiKv1yt2QxkZGZSRkUGrVq2iyy67jL761a+KMZw9ezZVV1fTtddeS2VlZeTz+YQgNZlMlJWVRcFg\nkPLz8+OYECVJmvDOyitTIttsNoHgYYHO6eb4WM54xMRaarWaTCbThGhshUIRlxjEaDQKBY65YqZC\nnkWjUfJ6vfTjH//4AykE05WZ/xDBRwqFAu+++y6Kiopw9OhRlJWVIRaLITU1FYsWLYJSqUR3dzcA\nYN68eTAYDLDZbMjOzsbevXuhVCrxzjvv4J133sHIyAiGhoZw4sQJcX0igl6vR39/P86dOweFQjFp\nO4gIp06dwtjYGIaHhzE0NHTetnPp6+vDnj17AABPPvkklixZIto9NDSEwcFBAIBer+cFEQqFQty3\np6cH7e3t6O7uRnt7O1wuF8LhMJRKJTQaDQDA7/dPaL9SqcTBgwfF9zabTVyXrw0AZrNZfB4eHgYA\n0T55ISIMDw+PT0DlxClIROLa//3f/43i4mKMjY1N6Ee73Q6FQoHDhw9PuIZKpYr7X61WIyUlBdFo\nFEuWLMGSJUvQ3t6Oxx9/HN3d3bjssstgMpnQ1dWF4uJi/NM//RMUCgV27NiBU6dOiWcxGAxwuVzY\nu3cvVCoV1Gp1klH7ZBWNRgOVSgWVSoX29naMjY2hoaEh7hk3b96MgoICHDt2DGq1GqmpqbBarSgt\nLYVGo4Hb7YZCocChQ4cwMDCA+vp6vPnmm2hpaUFvby96e3vR39+Pd999F8uXL4fNZgMR4aWXXsLJ\nkyehVCrx+uuvQ6fTQalUory8HEVFRdi/fz8GBgZw7tw59Pf3Q6/Xw2q1YmhoCMeOHYNer4der0c0\nGo2bS6FQCB0dHWhqakJfXx8GBwcxNDQElUqFzs5OOJ1OqFQqaDQaGI1GqNVqeL1eDA0NYXR0FGq1\nGn19fejr64NOp4Ner4dOp8P+/fsBAKOjo+jt7YVGo0E4HEZ7ezt8Ph8WLlwISZIQDAbh9XpFexoa\nGrB7925kZmbi+9//Pt58882PbkA/bk38o9TUWburrq4WmjpreCaTiUpKSqi1tZUA0EsvvUQ33ngj\nhcPhCVwYkwULJTNVTEYVK2c8nK7ZIdlxibY8bu/s2bPJarWK7WAyVEwymz4jS9iPwIRmUyFn5KaP\nxOtN9myT4bn/FtIzNivJt8C8k5rsfLkfpKCggOrr6+mKK64QTH+cKs1ut1Nzc7MImPnyl79M8+fP\npy9+8Yv02c9+lmbPnn1ec9UnpZaVlcWZ6VatWkWNjY307LPPUmFhIYXD4Ti/UzJN9N577yW1Wi0Q\nLsFgkDQaDeXk5AiGSwD0hS98gb761a+SRqOh0tJSGh0dpb1799LRo0eF/8JoNNKyZcvi0kPOnj2b\niouLRSo4p9NJNpuNmpubqbm5eUJ72PZdU1Mj5ngwGKSioiLy+/0iXkWSJAFRNJvNEwIKVSqVQOEw\nCVhWVhYZjUYqKCigkpKSpBxRnEsVGN/F3HPPPaRUKiknJyeOS+dC6nRlpoI1q7/X8teX8gMV1iS6\nurrQ398PjUaDbdu2QalUYmxsDFqtVmi3AHDbbbfh5ZdfhkKhwPbt2xPbEfdZrjmWlpbijTfeAAB4\nPB6heYyNjSEQCODkyZNCI2ctU67hTvHsSY9J9n19fT1effVVEBEyMjJw6NAhAIhrp7yYzWahRavV\naoyOjkKhUMBisWBgYAADAwNxx2s0GkiShN7eXqHh8DHcN+d7nsTzPmg5X9/V1tZi/fr1sFqtGB4e\nRl9fn3iG4eFh+Hw+AMDx48dRUlICi8WCkydPwmq1YsuWLbDZbOjo6MC8efPwhz/8AQqFAoWFhVi5\nciUsFgv+8pe/4IUXXoDD4cDp06cxOjqKzs7Ov+mZPu5SX18PALBYLDhx4gQ0Gg16enrgcDhw4MAB\nuFwuvPnmm3C73SAiWCwWnDlzBqWlpdi+fTva29uxdu1abN68GcFgED6fD/39/di3bx+uvPJKAMAT\nTzyBuro6rF+/HocPH8Zdd92F+fPnIxaLIRgMwmQy4a233kJpaSnWr1+PiooKnD59GqdPn0ZOTg4O\nHTqErq4uZGRkoLe3Fx0dHejt7QUAPPzww7jxxhvF89jtdpSXl+PFF19ELBZDf38/2tra4PV60dXV\nBa1Wi4GBAXR3dwvNfGRkBMD4PB0dHRXXslqtMBgMOH78OCRJAhEhKysLPT09AMbnY2VlJQ4dOoQj\nR47g5MmT4tzS0lL09/fD6/Wira0NRqMRhw4dEudeSCGi5CaAJAf+XVdMcxWz2WzC7s3fMVHR1Vdf\nTc3NzeT1esnhcFAsFqNwOEzl5eW0ePFiuvbaa4UmLc8OFI1GqaysLKmnm23ZfE4irlmv15NGoyGH\nw0G5ubmT5vW8EGehHNnByTrS09OpqqqKfvrTn1JraytVVVUJKGQiV7z8OvL/kzHOTVa5fxIdPMnu\nkUyLraysFKRQfNxk0Z/TqeeDgrHWPhnM0ul00o033kh2uz3OcZqojQaDQbELy8zMpHnz5n0gbeuT\nUJ999lkCQOvXr6cbbriBsrOzBcspo6icTicFAgFasWIFLV++XLwjCoWCMjIyBF7dYrEI9AtDZvV6\nPWVnZ9MPf/hD4SSV+6g4TyrXRH8OnzN79uw4R+kdd9whjlOpVCLTknxeLViwQLwTicnIJ0OI8fU1\nGg1FIhGSJInS09PF+7dw4UKaO3cuSZJEc+fOFdj7b33rW+T3+ykSidCMGTMoGAyS1+v9wKipacvM\nj1tof5TmF2Ace+1wOESEZWVlJaWmpoqtXnZ2NlVUVFBlZaWYLJdddtmUThiOmktmOuDJff31109I\ntzYV7HGy/yer8+fPFxzS3O7i4mK68sorafny5XTbbbcR8H60YKJDNrHtU1H6JlY5/TD/L3+5pnqm\nyRykic7WRGdvMmcsPx8/21Qon8TIX/l1vF4v5eTkUG5uLhmNRgGXlN+bMdLf+c53LmicPmm1qamJ\nYrEYDQ0N0dDQEN1zzz00b948ys3NFRhzh8NB4XCYLBYLrV69WrxbbMZg5JDL5aL09HS6/PLL6fLL\nLxfjf+mll5LBYKDly5dTTU2NWJjT0tIEdDgSiQiaAIvFIpQZprMNBAITlAalcjzZNGcNYjONnOKX\nYzs4oYXRaCSXyyVgjPJaV1cnnOQ8t1QqFeXn55NaraacnByqqqoSiWei0SjFYjGqra2lmpoaqq+v\nF/ltzWYzrV69+m/i3f+HF+qsGS9YsECgVTgMmoUA/2XbnVKpFBoaa7x8PTnXSGLuRq56vZ5aW1tp\n/vz5YjWezGYs5+6eSmOX47GVSmVcIl450RRnSgfexwyvXr1aCPXE6ye2a8WKFecNU5ZfI9nOQ6PR\nxKWYm+p+F1Ll/gi5LZ9favnLzW1gQcFJQfg4SZIEtjmxTc3NzXEcOE6nUzyPxWKhoqIiqq2tnRKy\n+mmos2bNouuuu45SU1NpaGiIgHH/g0KhiIN6qtVqkTM0EAjQbbfdRhaLhWbNmkWRSEQQd3HSdl40\neVxuvfVWys3NpXA4TLNmzYpDhCxevJjMZjM1NTWJOZ+VlSWghWq1esIiLkkSXXfddYIaWe7Hsdvt\ncbS2cmiyTqcT13K5XGLHxjQBbJ9XKBRUXFwsrmUwGOLQXUzpW1JSQqFQSPDVpKSkfCgxDf/QQl2h\nUMS9eIWFhYKDgkl+zGazSJRhMpniMqck0ziZY4K5xTmwhyMX1Wo1paamkl6vj2OPm0qYJYMd8l85\nR4r8d4Zf8UuV2E75PVtaWkSI9vmoC5Kl7ktW+dqJGgfzrSQLCprs2T/IuJ6vbXxMMiglh5kbjUYh\nXOQLQnp6OtlsNqqtrSWDwSACXtgBvXTp0k9VFGmyymYWi8VCK1asIJPJRA8++KDAqnu9XuHoa25u\nJrPZTBqNhvx+P7W0tNCiRYto1qxZNHfuXEF8xtfOyMigBQsWEDAOneVcpJFIhK6++moR6l9eXk5a\nrZasVmucMOQ0ccD7gtjj8ZDH4xHzmxUaSZJo5syZQmNWKpV0+eWXiwAjXtStVqtQGtLT0wVIYvXq\n1SJwjwm3GEDg8/nELsRqtYo2ccILm81G1dXVYgdQUFAw5S5yunW6MvNTCWn0+/2wWq3i//379+PE\niRMoLy9HamoqRkdHMTw8jLa2NoyNjWHu3Lk4c+YMAOD++++HSqUSzj+FQgFJktDT04Oenh4MDw9j\ncHAQY2Nj6OnpgcVigU6nQ0ZGBlatWgWdTodXXnlFnD82Ngaj0YiMjIwJztZEhx9/JnrfkcqOTobO\n9ff3i+NGRkYQCATgdDrjoHVjY2NwuVyoqqrC0aNHcfToUUQiEQFP43vLi9lsFp8Z3iZvq9VqFQ5i\nh8OBvr4+BAIBBAIB+P1+9PT0xLU72T34GvL7TFaUSqWo3AZ5X/F38jI2NgYigtFoRHd3NxwOR9yx\nfX19ICIBsVOpVBgbG4NSqYROp8OhQ4ewZs0a7N27F319fRgbG4NOp0N/fz9GR0fx1FNPYffu3dDp\ndJO2+5Ne/vznP+Pll1+G1+vFn//8Z0SjUWzevBknT57EL3/5S3R1dcFgMCAWi+EPf/gDli1bhuHh\nYeTm5iIcDqOnpweSJOHFF1/E8ePHsXXrVoTDYYTDYXR1deFPf/oTvF4vPB4PHA4Hjh49ipycHDz/\n/PPIyMiAwWDAuXPn4Pf7EQ6H0dTUBLPZjKamJhw4cACXXHIJlEolMjMzEY1GcfLkSZw8eRJGoxF+\nv1844XU6HXQ6HcbGxvDWW2+hrKwMb731FtxuNwoKCqBWq+FwOBAOhxGLxUR7fv/736OhoQE///nP\nMTw8jOHhYRw7dgw+nw8pKSnw+/0AgLNnz6Kvrw8zZ86Ez+dDKBSCWq1GT08PTCYTNm3aBL1ej127\ndiEajaKrq+v/bAw/NegXn8+Hs2fPAgAGBweRlpaGo0ePit9LSkoQCoWwadMmBAIBbN++XXi1TSYT\nBgYG0NbWJrzekiQJxMqiRYvw1FNPcXuEcDGbzQiFQmhra0NZWRn+9Kc/TYrwSElJEQsHXwfABEEl\nL/I28DksWJVKpXw3AwBIS0vD6Ogozpw5g5GRETidTuTm5gIA3n33XbS3t8NkMuHs2bMThKTdbsfY\n2Bg6OzuhUCig1WrF4geMY9M7OzvFOcFgUPR3X18fVCqVODYzMxMHDhyYFsLnby2MaJH3ES8qWq0W\nZrMZXV1dGBwchCRJSElJwbFjx8S53J9cX331VdTV1cFkMqGnpwd2ux3nzp1DMBiEw+HAW2+9JZBN\nn9bi9XpRUFCAjRs3oq+vD7W1tbDb7di5cycWLlyI119/Hbm5uXj22WchSRIcDgduueUWXHvttfB6\nvVCpVEhJSQEAtLe3i0Wwt7cXBoMB+/fvh1arRVZWFpYsWYJ///d/F+ghVqhGRkagVquh1WphMpmQ\nlZWFY8eOgYjgdruhUqlw+PBhSJIEYPw9OnPmDEKhEHbu3IlFixbh6aefxs0334xDhw5h3759OHfu\nHKLRKNrb23HixAn09vaisLAQr732GgAgKytLIG1ef/11IcA7OjqQk5ODrVu3Ckz+8PAwTp06hTlz\n5uC9994Ti9GBAweQk5ODI0eOwGazobe390NDRtE00S+fGk39xIkTsNvtsNvtCIfDQqArFAqkpKTg\nrbfewpNPPonTp08LiOGpU6dw8OBB7NixA0ajEaOjo9DpdNBqtVAqlULwHjx4UNyHiBCNRnHTTTeh\nu7sbRqMR1157rYAEjo6OYmBgQGihK1euhEKhEAKdBUmiQJYXk8kEABMCk4gIKpVKCBU+X6FQYOHC\nhTh69ChOnDiB4eFhmEwmOJ1O2Gw22Gw28cwsiFnwcTl37hxsNpv4bWRkRAhLFnwKhQImkwlGoxGB\nQAAVFRWoqKgQgVRarRYAcODAAajV6jiNnbV9lUqFysrKDzjKE8vw8HDcLkPep4ODgzh9+jQGBwfh\ncrkQCARw7NgxmM1mmM1maLVaDA8PQ5IkmM1mOBwONDc3o6SkREDOVCoVcnJycPjwYXGfQCDwobX/\n761oNBpYLBa88sorGBsbQ3l5OZRKJY4ePYrGxkZ897vfRUNDA0pLS6FQKNDV1YWhoSH8z//8D1wu\nF9LT02E0GlFcXIx3330XHR0diEQiiEQikCQJ3d3dCIVCyMjIQH5+Pp5++mn84he/gMfjwbJlyzA6\nOiqghStWrEAoFEJmZqaAjhqNRigUCnR0dOB73/ue0MgPHTqEoqIi7Ny5E//8z/+MgYEBEBHS09OR\nlpaGiooKdHV1oaurC/v374dSqYTBYBDjHA6HMX/+fHzta1/DuXPn8NWvfhWhUAihUAh+vx9bt25F\nVVUVbDYbjh8/ju7ubrjdbmzcuBG7du0SMGav14u9e/eiuLgYx44dQ1pa2v/9IH7cNvMPy6aeDK0i\n5wlnmxvbgjUajbCZyWGMbGtVKpWCGS47OzsuDJ+daU1NTSLjC4A4R8x06HensrczD8Z0nx8YDxzi\npATAOJfJAw88QA888EDS+8lt+vybHFrG9/d4PHG2dDkFLv5qf03kmbfZbHGOKnkyBL73VM/CSRvk\n/XghCTz4Huww5T656qqraNGiRbRo0SJBB8D+FLfbTV/84hcFze+8efMEtcLatWsFe+ZkSRE+yvp/\nhbZRq9XkdDrJ5/PRnDlzKDU1lZqbm6mmpoY+//nP07Jly0in01E4HKbCwkIqLCykaDRKW7dupeXL\nlxPwPjTQZrMJmlmTyUShUIh8Pp8I/rn++usJGEeoVVdXU2ZmJl111VV0zz33kNlspvr6err11lvF\n9crLywW8sbq6mmw2m+Bk+td//Vfy+XyiDTt27KAf/ehHdOmll9LDDz9Mc+bMoauvvpouv/xyqq2t\nJZPJJCg3eG5kZWXRmTNn6Ec/+hG1traKeVJcXExms1nY1uU0v3Kbv9PpJIViPFepUqmk/Pz8D3Vs\npiszPzXml8Si1WrhdDqFPezUqVPQaDQoLy/Hpk2bMDIyAoVCgWAwiEOHDokw/8kKb/OGhoZEgNFk\nRafTxZkuZM8itF6dToeBgQGUl5dj69at4nceD61Wi3A4jL6+Ppw8eVIEWXBJNDvIi9vtxg033ICH\nH34Y2dnZAIC5c+fi/vvvn3Cs/J6SJGF0dBSjo6NQKpUwm81i62iz2aBWqzEwMIDBwUEMDw9Dr9cD\nAObPn48nnnhCXGMq6gOFQgGlUgm73R5njuJnGh0dnZZpQ95uuckl2XwuKirC6dOnkZaWhkAggOPH\njwMAOjs7MWvWLPT39+OJJ57AuXPnMDAwgJkzZ2Ljxo34wQ9+gGeeeQbPPPMMUlNTEYlEEAwG8frr\nr2Pv3r2T9v8nuahUKixZsgSvvvoqWltbsW/fPhw5cgQ5OTk4duwYRkdHYbPZYDKZ8Oyzz8LhcECh\nUKCxsRFbt25FXV0dNm7cCJPJhGXLluF3v/udmEOSJMHtdmPnzp348pe/jGeffRZ79+7FkSNHYLVa\n0d/fj66uLkiShEWLFmFwcBClpaX49a9/jYGBAbS3t+PcuXOQJEkE//DuUpIk7Nu3D0ajEbNnz8bP\nfvYzXHfddbj//vtRVVWF+fPn4ze/+Q3Ky8uxd+9eBAIBbNq0Cf/2b/+Grq4ufOc734FKpcIll1yC\n733ve1i0aJF4LwsLC7Fp0yYQkTDLORwO5OTkYPPmzXC73Whvbxc736GhIXi93jgqkQ+jTNf88qkS\n6i6XCwBw+vRp8V1mZiby8vLw3HPPARh3OMqjSGX3iYsUNRqNsNvtOHr0KJYvXy5MMFu2bAHwvgBS\nKBTQ6XTCCadUKlFaWopdu3aht7f3vLbzxMVEqVRi2bJlePLJJzEyMoKamhq8+uqrcLlcUCgUgocE\nmBj5xqWkpARvvfUWHn/8cXzta18DMO4svvrqq/Hwww8LwcomnMS2ZWRkoK2tDVarNc7W6XK5cO7c\nuQn95/F40NPTg97eXjgcDpw9ezapP4CIJkTxcmFzDT8Pm3IGBwdhsViEo+l8i0aywuc7HA50d3ej\nvLwcwLjj9s0330RnZyeWL1+Ovr4+pKSk4M0338SRI0eE7f0LX/gCnn/+eXR3d+Ppp5/G7373Ozzw\nwAPo6Oi4oHb8PRc2F95111144403MDg4CKvViqeffhrZ2dlwuVwYGBjAT3/6UxQVFeG6667DE088\ngZGREfT09KCwsBDvvfceRkdHEY1GsXPnToyNjaGoqEgIN6PRiIMHD6K7uxs6nQ7hcBiDg4M4e/Ys\nVCqVUJRSU1MRDAaxadMm3H///VixYgUefvhh/OUvf8G2bdtgsVhQUFCAI0eOiIV1aGgIbrcbPT09\nOHToEBobG9HR0QGVSoUZM2bgjTfewK5du6DValFSUoJt27YhNzcXvb292LJlC/Ly8oR5TaVS4ezZ\ns2LBWL9+PbxeL/R6Pdra2qBUKrF69Wo89thj8Pv9SE9Px4YNG+ByuYTsYb/Sh1n+IYX6vHnzAEBQ\nAQwODsLr9WLHjh0Axkl+mJjKZDKhu7t7gjCXa3vy8P/EolarYTQaMTg4KGzoo6OjIvyeV3QuHLpu\nNpvF93wffqEcDgfOnTuHkZERXHPNNdizZw/Wr1+PSy+9FL///e9hNptx5swZKJVKEeY82fg99thj\n+MxnPoPvfve7AIB169YhKysLR44cwdDQUFJnHz97cXExtm/fLpzNbMvnHY/D4YBKpcJ7770nzr3l\nllvw6KOPIicnB2fPnsXx48fFjmRwcFC0MzU1FceOHRP3ki9MSqUSs2fPhlarFYRHlZWV+O1vf3v+\nwce4wGcipsTnkve3fNfFFAlEBJ/Ph87OTuh0OlRUVECpVGL//v2IxWKorq7Gxo0bcfDgQdTU1OCH\nP/xh0sXpk15Onz6Nt99+Gz/72c8wMDCARYsW4dZbb0V3dzcGBgZQXFwMj8eDvr4+eL1ebNy4EaFQ\nCABw8uRJ2Gw29PX1wePx4OWXX4bf70dOTg4AoK2tDW1tbViyZAn27duH/fv3w+12Q6fTCR9YZmYm\nDh48KEjBxsbGcOTIESiVSjz22GO4+eab0dvbiz179sDj8SASiQAADh8+DI/HA7vdLt7HzZs3w2Kx\nYOXKlXjuuedw/PhxZGVloa2tDZIkYWBgAMFgEMePH0d+fj4OHjwoHJ6PPvoofvGLXwAAtm/fjoyM\nDDz//PMoLCzEsWPH4HQ6sXPnTjQ2NkKpVOKVV15Ba2urACO88MILH/rY/MM5Si+Wi+ViuVgulk+Z\npp5YotGo0AYGBgbQ29uL1tZW/OpXv0p2n2nD75IdmwgxTE1NRXFxMf74xz+iqakJzz33XBxpEJtA\nkplP2N4OjEMNKyoqcPLkSWzbti3uOLVaDZPJhI6OjgltKi4uxrZt24RJ6oknnkBTUxNGR0cFTO98\nz5adnY3jx4+jt7cXWq0WIyMj0Ov1GB4ehkKhEG0sKirC9u3bUVhYiLfffhvAOCyOEQuJhXczU/X5\nihUrAAC//e1vp21uSTRH8W5EHhOgUCjgdrsBjCOmVCoVwuEwdu/eDb1ej5GREcycORPFxcXYvHkz\nNmzYIGzIBw8eRDgcxmWXXYZHHnlk0j78pBX5ONx+++04cuQIduzYge7ubnR1dSE7Oxsmkwmvvvoq\n/H6/2KEtX74cv/rVr+DxeJCTkwO/34+XX34ZPT09Ih6ks7NT+F6MRiNOnz4Nh8MBv9+PjRs3IhwO\n45133kEwGBREYkwcNzg4CK1WC7fbjZKSEuzevRuRSAQdHR3QarUCyQSMm0PZfPbOO+8I2t5z584h\nLy8PX/rSl3DllVfC7XYjGo0K1Ft6erowf5rNZiiVSrS3tyMYDKK2thYA8OCDD+Kee+7BCy+8gJ6e\nHrS1taG3txd1dXXYs2cPXC4XdDodzp49i+7ubhQWFuKPf/zjhz5O/5DmF4YCys0eHo8HAwMDyMvL\nw8aNG+HxeJCVlYUNGzYkdbbJGQtZIMjhf3y8wWBAX18fIpEI9u7dK2/vlIuDXGAnHstBP0NDQ3GO\n0Egkglgshqeeego2m03YKPkYuZ1a3s5wOCwE2BtvvCEcmrm5uWhra5vQDv47f/58dHd34/XXX4+z\n92s0GkQiEezcuRPA+9C+I0eOiOsEg0H09/fj1KlTcW3hbS8RIS0tTZyTrDDcDAAqKirwyiuvQKPR\nYGRkRNjlDQYDent74XQ6oVAoBJc9Myxye9Rq9QQcu8fjAfC+UDebzRgcHBR83ZFIBH19fdBqtejo\n6BDmtJGREWH3dbvdcf6NT3JRq9UCZnrq1ClUVlbijTfegMPhECaM/Px8vP766wiFQti1axeA8XFq\naWnBiy++CJvNhjNnzqCgoAAejweHDx9Gd3c3AoGAcIirVCrMmjULTz31FDIzM2G32/Hss8/CYDDA\naDSivb0dKSkpOHXqFLxeL1paWrBr1y6MjY3Bbrdj7969wrzCTnteMNjcyu/X2bNnodFoYLVaYTab\nMTAwAKVSKQIJc3Nz8corr2BgYABer1fALLdt24Zjx46huLgY99xzD4DxOJX29nbcfPPN+MEPfoBb\nbrkFTz75JN577z0Eg0Fh+mlubsYbb7yBPXv2COXtwyzTFeqqr3whuJe9AAAgAElEQVTlKx/6zT/M\nct99933lfMf4fD4hyEdHR3HnnXciMzMT27dvR29vL6qqqtDX14cTJ05Ar9djz549IppQr9dDrVZD\no9HEOerkRaPRCPszTyoetPb2dvEdl8RIR3kZGRkRUZI6nS5u8JVKpQi6YHQO3394eBh+vx/79+9H\nfn4+VCqVwNkmc3byYrZ7924cOXIEJpMJfr8fVVVVgnJU7qSV48qHhobQ19eH/v5+WCwWYaMmGk/w\nkZ2djaamJmzduhXd3d1x905NTcWRI0fEtVJSUtDX1yeShxiNRjQ0NGDXrl1id5NYsrKycOLECQwN\nDeHgwYNoamoSC4LP50NHRwcCgQAUCgVycnKwb98+9PT0QKVSITMzE+np6cLJmSy5BjBuT+cdgHw8\nR0ZG0N7ejoGBAYyNjaGgoAA7d+4UVLQjIyOQJElEnH4aiiRJCAQCUCqVePPNN7Fjxw4QjSdV6e7u\nht/vh9PpxN69ezFnzhx0dHSgq6sLRIQjR47A5/PBZrMhPz8f/f39MBgMkCQJnZ2dIqhNo9HA5/OJ\neWsymbBjxw6EQiEcPXoUmZmZaGxsxJYtWyBJEsrKyvDMM88gIyMDHR0d2Lx5M+6++24MDg7i0ksv\nxf79+9HR0YF169ahrKwML730EgYHB3H48GF0dnYiEAjg4MGDIohubGwMBw4cwLFjx3D27Fkx9ow7\n52CmwsJCrF+/HhqNBq+99hpeeeUVvPPOO3C5XHjjjTdQXFyMa6+9Fj/60Y/EnLDZbEIh2Lp160cW\ncPeVr3zlvukc96kQ6izQJUmCUqnEa6+9BiJCWVkZTp48CYVCgaNHj2JgYAB9fX0izD09PR1nz57F\n8PCw0AKBcc24vb1deLzl2Xt4UrIQV6lUaGhogFqtThoxyp+5yh2ULEg40InRM/KFpaysDPv27cPx\n48dx++234/nnnxcaIgeKdHd3Iz09HTk5OTAYDLBarTh79ix6e3uhVquhUqngdDpx5swZsbBptdq4\noCp5lCoLyr6+PgFxlBetVov9+/cLxI/D4UB/fz8kSRK85Nw/fX19UKvVAmkzNDSEXbt2Ce2YXzp5\nUavVAsKpVCqRn58vFrZQKASz2YzPfe5z2LVrF1577TVxPhHh9OnT8Hg8MJlME8wjHGXa398vXmqz\n2YyhoSEYDAah0Y+NjYkMOJmZmVCpVDh16pTYDWm1Wmg0mgtG4fy9FkZ6jY6OIhwOQ6/XQ6FQoLe3\nFyUlJTh27Bj27duHaDSKV155BW63W8BdR0dHUVpaCovFgv7+fgFCGBkZQVFREdra2mA2myFJErZu\n3YqdO3eirq4OO3bswB133IHHH38cgUAANTU1+PnPfw673Y60tDTs3bsXDocDo6Oj2LVrF5YtW4Yf\n//jHMJlMQvlaunQpfvnLX2Lbtm1wu93Ys2cPampqcPToUXi9XhQXF+PEiRMIh8PYunUrnE4nrrzy\nSuHQ3bVrF0wmE4LBIN5++21UVVXh1VdfxdKlS7Flyxbs3r0bbW1tcDgcmD17Njo7O/HZz35WtOHt\nt9/GZz7zGRw8eBDz5s1De3s7Tp8+/ZFo6cD0hfqnyvwSDAYBALm5uXjttdfg9XphtVoRjUaxZcsW\nYTZgaJ5Op0NPTw9SUlJgNpsxPDw8IRKVozPlZgx5icViAqlhNBrj8OTJTDeJ0L6cnByRoo7P4WO5\nyG3FK1euxOOPPw6tViu2uXxvRn5cddVVePTRR2E0GuO0bGB8V0NEqKmpwdatW8X5rLUzaodhjcC4\nqSkQCAh6ATatMGoncbfBiJfR0VHxnIk+h8WLF+PJJ5+ERqMROxe32x1nyknsB4ZYRqNROBwOATvk\nsHIuyeBkclOMfMGVJEkIa1YKeKs+NjaG1tZWPP3003A6nWLOeL1eDAwMiN3AJ71oNBoRz9DX14dD\nhw7h/vvvF3bntrY2oUiwP4b5V5qbm/Gzn/0MKpUK69atw3333YdYLIbR0VE0NTXh3LlzcYtrZ2cn\nDh48iP/8z//E+vXr0dXVhd27d+Ott97CyMgIzpw5g/z8fJw4cUJQDoyNjWH37t24+uqrsW3bNnz7\n29/G//7v/+LRRx8V7/zp06dRVFQElUqFF154ATqdDp2dnVizZg3279+P7u5u9PX1YXh4GOnp6WIn\nwkls3nnnHTQ2NmLTpk1C6eJFu7m5GU1NTXj77bfxk5/8BJIkIT09Xdyjvb39AyW9uNDyD4d+icVi\nOHz4MA4fPoyMjAwYjUaEQiEUFBRg9+7dIow3EAjA5/NhZGRE4FDPnDmDtrY2YZ8DIAQfZ87Ztm0b\ntm3bFqd1A4jLj5kYIMSaN3+W/x0cHIRCoUB3dzfmzp2LuXPnit/NZjNsNhskSRL0BUzYdeTIETz0\n0EMYHBzEmTNnhO25t7cXfX19WLJkCU6dOoWWlhZYLBYhSMPhMBoaGgT5EePeNRoNDAaDMMP09PQI\nEwz3R0pKCjQaDTo7O8XLzdoS+x+4PxJNE/xisKbOx23atAlKpVIQpHFIv7zvEhUObvfixYtx6tSp\nuMwzPJbAeMg3AJF3lXdImZmZ0Ol0wndBRHHa99DQkNhhcPsdDgccDge6urowNjaGvr4+SJL0qRHo\nAIS/o62tTcATH3zwQdx+++04ceIErFYrrrrqKiiVSmRnZyM3NxdjY2M4fvw4fvvb3yI1NRV6vR6/\n+c1vMGvWLOFcP3DgADZt2oSdO3di586dwnY+c+ZMzJkzB5s2bcKhQ4eEgG1ubsbo6Ch27twJpVKJ\nXbt24e2334bRaMS6devw/PPP4+jRo7jzzjuxYcMG+P1+uN1uuN1uqNVqPPPMM9iwYQM2b94Mu92O\n3NxcETx16tQpkdP24MGDOHXqFPbv34/Ozk50dnait7cXu3fvhlqtFlwvnKN0eHgYRqNRKCaDg4PY\nu3cvtm/fjsOHD/+fCPQLKh9GKP9HWTHNEFrOXM71pptuoiVLllBLSwutXr2a8vLyRAILt9tNa9as\nEeHe8iw38nDsZBmPkh03nWMmO16euefzn/88mUwm0S6m3wXGw+Y5nD0SiVBqairZbDYqLS2dcG0O\nz3e5XBSLxeJ4qjlU/7LLLqPS0lKqqKig++67L+58pgRobW2l0tJSuv3228nj8YiEAYn3k9MNyKkN\n5N8nXr+2tnZa/cNVft2dO3fSSy+9FHcu95UkSZSTkyNC+uVVnkF+svYn1tTUVBEWzm3IysqakPnp\nk1qZStrr9ZLX66VwOEyVlZUUCASotrZWjDmAuM+cVMJoNFI0GqXMzEyqqakhAFRUVEQtLS3U2NhI\nsVhMUD4UFhZSc3MzBYNBSklJoXA4TMA4/QNzlmdnZ5NeryeTySToanNzc0Vu2UgkQkqlktLS0mjl\nypVUU1NDNTU15Ha7ae7cuZSenk7XXHMN1dXV0cyZM8nlcpHL5aLc3FyRj9jtdtPs2bOpoaGBWlpa\nxDsRDAbJYDDQihUrKC0tjTZs2EAbNmwgt9tNbW1tdMMNN3ysYzVdmfmp0dR9Pp8g94lEInj88cf/\nP3vvHR53daWPv5/pRdNnNJqRRr33blmyLNkqbnKRjRsxLgFjSowNLIaQZ/k6kM0mZIEQFpNkYRdC\ngAC2AWOajQGDu7EtuUqyerV67+X8/hD3MiPJxBD4kYDP89xHmplPvfOZe899zznvC4vFAo1Gg127\ndiEvLw+hoaHIzMxEU1MT3njjDc4uGBAQgKCgIB4sZbZ48WK4u7tDrVZDJpPxohWRSMTZ5BQKxZSB\nUfaeM4yg0WgmbcsCiIIg4LHHHuMq58CX3i27r7a2Nuh0OoyMjMDd3R06nQ4lJSWc/sBiseDuu+9G\nVVUVgoODYTabUVxcjOLiYmzevBnZ2dlISEgAME6EFR0djRMnTuC9997jrHoAuIeuUCgQHR2NF154\nAT4+Pjh06BAiIiI4fS8z9jAx2MX5/an6ZWxsDF5eXiAiTgfMVjVqtRqpqamT9hsZGYFcLkdGRgbi\n4+ORlZWFFStWuARbGWZfXFzM7xP40mNnqx3n79L5WmUyGRQKBdLS0pCZmQl3d3eOCzMPbfXq1Who\naHAhEftXtuHhYRiNRly5cgVXrlxBSUkJfHx8UFtbi87OTtTV1SEkJARhYWH4/PPPMWfOHHh5efGC\nvtHRUfT09PD4g1qtRkBAAMrLy1FdXY22tjYkJiYiMTERbW1tOH/+PPz8/BAaGoqmpib4+vrCYrHg\nwoUL0Ol0aGlp4YyZer2e0zrMmTMHycnJaGtrQ1BQEHx9fZGamspXefn5+bh06RLCwsJ40dzHH38M\nh8OBpUuXIjg4mENvs2fPxtGjR/Hpp59Co9Gguroajz32GA/qvv/++5gxYwbS0tKQlpaGpqYmhIeH\n489//rPL7+Sf1X4QgVJgvJqNLZFvvPFGqFQqNDY2YsaMGdBoNDhw4AB0Oh1OnjzJGQhXrVqFS5cu\nobKyEm1tbbBYLFi6dCliYmKQk5MDT09PvP322/xhYPCBRqPhcIVz3rlzMHSqAW1oaAiCMC7uPDg4\nyIOuKpUKCoWCD/xdXV1cNFmv13M2PJaL297ezvN2LRYLPDw8UFhYyGlEN2zYgMbGRk55qlarsW/f\nPgwODkKpVKK6uhpeXl6QSqVYsWIFdu3axbmqpVIp1q9fz/mgbTYb58Do7OxEc3MzzGYzp1Flwdr+\n/n7eFwkJCTztkvUHM/aalYUz2IP1a29vL5qamngMgU0eDKqpqqqCzWbDAw88gD/84Q+wWCwwmUzo\n7u7Gc889h/j4eJw4cQJms9lFfJvtD8CF34ZNRixDQiwWo6KiApWVlYiMjERqaiocDgcfxNhA39bW\nBpFI5BJE/1c1Z/jgd7/7HeRyOex2O3/uKioq4O7ujo6ODrS3t/MgtJ+fH4cJo6OjceDAASxatAhH\njx7l2TRubm6IiIiA2WzmQfWmpibExsbCbrfj8uXL6O/v5wFshUIBpVLJ6ZJVKhXGxsZQUVHBKbLL\nyspw3333YdeuXcjNzUVwcDBqa2vx6KOP4vjx49Dr9XB3d4ebmxtEIhGkUik+/fRTyOVy6HQ6VFZW\nws3Njac6njp1CnPnzkVnZycGBgZ42iNjNAW+/J1PrFb+/9OuNVD6g/HU6+vrYbFYYLFY8Prrr8PL\nywtpaWloaGiAIAgICAiA3W7n24tEIu7NMxrRxsZGvPjii3j55ZdRUFCA3/72t1i9ejWALwcCsVg8\nJT8y81adKQcATOnVMh4Th8OB5ORkdHR0oKOjg5P69/X1ISMjAx4eHmhtbeXbM3xaLpfj/fffh91u\nR2NjIy5cuABBEHD8+HFUVVXh97//PU6fPo24uDiMjIxgZGQEPj4+iIuLw7Zt20BE0Ov18PX1hUKh\nwF133YU1a9ZAJBLBYrFg5syZ6Ovrw9GjR2G325GWlobq6mp+H2wQ6O/vd8kkAcYH4VOnTrkIVEyV\n+ldYWIjExEQMDAzwCXPifbJ7BcaDxawOYXh4GH/84x8BjOdVV1dXw2azYcOGDTh//jz6+vpw8OBB\nfj1arZZfw8KFC12+CwCcboHlOjNraWnBwYMH8corr8DNzQ0OhwMfffQRdu7cicbGRvj4+Ey6r39V\nU6vVUKvVkMvlaG9vR3V1NZqbmxEZGQm9Xg+xWIwdO3bwtMGIiAieTx4QEAClUon4+Hi0tbVxcQiW\n9VJTU4OamhpcuHABAwMDUCgUOHfuHAwGAw84BgYGYnh4mMdtxGIx7rzzTtTU1EAul6OqqgptbW08\nwyw7Oxv19fX4/PPP8fnnn0Mmk/HsqDfeeANlZWU8395gMCA/Px+NjY1oa2uD1WqF3W5He3s7mpub\nMXPmTP7dWywWqFQqlJSU8N80K+D7V7EfjKcOABEREdDr9SgqKkJqaiqampqQkJCAqKgoHgD8/PPP\nXfKVu7u7MTo66vJjHhsbQ1VVFUZHR1FYWIiZM2eipaWFi1/ExcXhypUrU3rkbGBnn7ECJp1Ox88h\nFothtVpRW1uLyspKZGdnw9/fHxUVFZBIJHB3d0dMTAyCg4MxMjLi4vUC4F4s43Rmg+HEyUMkEqGo\nqAhdXV3Q6/Xo7u5Ga2srqqqqUFBQgNLSUvT29qKmpgafffYZh0RKS0tRU1ODkZERHDhwAPPnz+dC\nAqw4ilWYAl+uQJxNq9VOygRiaYOsz1pbWzkzJHtPpVJhZGQERqMRSqUSPT09PDVtcHCQV6O2t7fz\nHHgA6OrqQnZ2NsxmM8rKyuBwOPjKjXHdxMfHQyaToaqqin8/LB3T+TrNZjOHoGprazkrJatnGB0d\nhd1uR0REBM6ePXutj+c/tTGVH7VajTlz5kChUKCxsRFRUVHQarUICAhAV1cXamtrERkZibq6OuTl\n5aGyshKjo6OwWq3cmxaLxfD29uYT7tjYGLq7u6HVarmnPzw8jPb2drS1tfGVZ2trK8RiMebNm4eL\nFy9i4cKFiI+Px4ULFzibalJSEu666y7cfvvtePfdd/Hss8+is7OTpyRfuXIFFosFH3zwAVJSUjA4\nOIi+vj64ubnh7rvvxrlz53hwVKVSobq6Gh0dHRzqZM+Tc8Ha9+mdO9uPMqXx8ccfBwD84he/wC23\n3IKCggLceuut2LFjB+6++2689tprKCoqQkxMDN58800MDQ255Kc7G1u2DQ4OQq/Xw8PDAwBQVFSE\nuXPnYt++fVctbJnqNQBeoNHY2AiDwYCioiKo1Wo8++yzAIAHH3wQra2t6Ojo4AyPMTExKCkp4QMP\nOyY7/kSFp4l2yy23AAA/x9jYGKKiohAVFYW//e1vfLvMzEx4eXkhMDAQFRUVeOONN+Dn58chHqlU\nCr1ejzNnzly1anYi3ai/vz9n0mP7sBS1qz13rFLX2aaiNfD390dbWxsUCgWGhoaQm5uL7u5uVFRU\noLW1lefLKxQKTpI2NjaGefPmce//9OnTLtlLE/tVJBKho6MDo6OjkMlkPJVvbGwMa9euRUFBAex2\nO95///2r9v+/irHn+8qVK9Dr9RwDVyqVuHLlCmJiYnDhwgUkJiZyAi6NRsOlAxk0Z7fbefbWvn37\n0NzczMvtx8bGIJFI0NbWhtHRUTgcDpw6dQparRaXLl2Cp6cntFot6uvrERoailOnTmHWrFnQarU4\ncOAAlixZgr6+Phw7dgybNm3C448/jry8PADjRW8333wz3n77bTQ1NUGn0+Gpp57CzJkzUVhYiBMn\nTiAkJARGoxEKhQLl5eVoaWlBYGAgSktLvxZNyPdl15rS+IPy1AcHB1FcXIwVK1YgJCSEBz6ff/55\nhIaGoqKiAjabDa+99hr3LCdCAyzVjRWXeHp6oqOjA319fejq6oJYLEZRUdHffQCmCp4ODAygpqYG\nbW1tiImJ4fnvv/nNb/Dyyy+jsbERPT09LvCD2WzmXBvMi2XXGBERgbKyMqSnp18VFmpqakJpaSk8\nPT1hs9m40k9ERASWLFmCd999F8A4Xp6fn4/du3fD398fhw4d4oUUXV1dWLx4MXQ6HYjIJfUQAC8g\ncvbM/fz8UFVVhZUrV3I+mIn9IggCfH190dHRwXlX2GvWvzqdbhLFrVKpRHNzMy8my87O5imrhYWF\nMBqN3OvcuHEjx1C7urpQWlqKoqIiFBUVYdOmTSgvLwcRcc+MeePBwcEYGxtDe3s7r7AFxifVBQsW\noLW1FaOjoygtLf2Xx9UlEgm6uro4rBYbG4vq6mpotVoUFRWhvr4e2dnZSEtLwyeffILbbruNUwaE\nhISgs7MTfX198Pb2hkQiwc6dO9HV1YXR0VGYTCbU1dWhubmZUwkYDAbo9Xrs3bsXAQEBKCkpgUQi\nQXR0NEZHR6HT6VBRUYH09HQ0NzcjLy8Ply5dQn5+Pl5//XXk5uYiLCyMS+O1t7fDZDKhsbERtbW1\nHI45cOAApk+fzvPc2cDN6iySkpJw6tSp77n3r91+VBWlzBYtWgSr1YrOzk5s2LAB7u7umDFjBt59\n911YrVa8+uqr6Ovrw4YNG9DT04OBgQGXpXdKSgpqamoQGBgIDw8PtLS08HJovV4PqVQKs9nMvcbg\n4GC0t7dfdYBneeBs4hCJRFi9ejVWrVqFP/3pT6irq0N1dbVLRSmrvgQAHx8fztPCRDecg7GNjY1I\nSUnBkSNH0NnZCR8fn0kDIONMUalUCA0NxWeffYbIyEjIZDIcPnwYCQkJOHfuHMeVGQ0Bq8plE4hM\nJkNdXR3CwsIglUoxc+ZMDAwMwGAwoK2tDWlpaWhsbORebnV1NYjGq+6sVisf8FlfMVHpjo4OLFq0\nCDExMTh37hza2tp4PzCKYWdoTBAElwIiIkJxcTGGh4fxhz/8AX/729/Q2tqKmJgY+H6hSXv58mUO\nUW3duhWCIMDhcKCsrMxF7CInJ4d7bTU1NXj44Yfx5ptvYmxsDAEBAfx7nzlzJgwGA44ePfqD4H8Z\nGxvjVbjLly9HQUEBRkdHkZaWhpKSEl5s9e677yIxMZFTCbS0tMBqtSIjIwOlpaU4duwYAgMDERMT\ng7q6OnR0dCA7OxufffYZuru7YbfbMXv2bFy5cgVlZWUQi8WIiYnB+fPnIQjjwuCDg4Po6enhohaM\noz85ORnPPPMMFi1ahPr6ely5coVzDXl4eODkyZOw2+24++67cc8990ChUODWW2/FG2+8gZ6eHly5\ncgVVVVWorq7mq87vsqT/u7BrHdQlf3+Tfx379NNP+f9LlizBpk2bOL8xw4STkpLw/PPPc2ZDYNwz\nWbNmDUZGRnDx4kWUlpZCqVRCr9cjICAAZ86c4T/e5uZmPgBXVVVdlf+DLdPZgMGEp19++WWo1WqX\nbZ0zPJgGaUxMDE6ePImqqirk5OTgxIkTnGfFGb5gla5EhJycHPzP//yPyzWwgai1tRVlZWVYvXo1\nGhsb8be//Q1WqxUnTpzgJfiMofCFF17g18/ur7KyEr6+vti1axeeeuop3H///TwtMD4+HocOHYKb\nmxuGhobQ0NAADw8PNDQ0QCqVTrpfAC4T3Z49e/Dggw+6kJgxvJ4Fq9jk4sx7D4x77YzOICMjA4WF\nhZg1axZOnDgBg8EAmUyGOXPmoKmpCTU1NXzJDYxzzjsTrO3fv59nI4WGhuKOO+7Afffdh6effprD\nSgcPHsSLL76Ixx9/HOfOneMeYklJCeRyOVpbW6d8Hv6ZTSqVcufmtddeQ2BgIPr7+1FUVITR0VG0\ntrbCy8uLpxvefvvtyMrKwsmTJ9Hc3Iz3338fH3zwAebMmQM/Pz9cunSJVwbv2bOHQ4CFhYUcUy8t\nLQUA/nyGhYVxbqD4+HgcO3YMcXFxvIDwtddeQ2JiIl599VUuRC2Xy3lFqSAI+OUvf4lPP/0UIpEI\nCxYswO7du5GUlITPPvuMVx13dXVBEATk5OTwjKYfnH3fxUXfVvERAPL39yd/f3+6/fbbCQCdPHmS\nXn/9dbrxxhtp+vTpZDabadasWQRM1us0m82kVCoJAC90AEDz58+nuXPnTnk+VrQUHh4+6bOvKqaR\nSCQUEhJCcrmcF1gAIDc3N1KpVC77ikQimjlzJj+mm5sbCYJAIpGI34PRaOQFSyKRiAwGA4lEIpJK\npbywRqVS8QINVjjyVY1dg7MuaHJyMm3evJm2bNniUgzEjse0Hqdq+fn5LvckEolIo9GQIAj8HDqd\n7qr7s3u1WCyTrtPHx4esViulp6eTu7s7KRQKUigUJJFI+He6c+dO8vT0pPz8fN4kEomLdq1OpyOx\nWMzf+8///E8CQB0dHWSz2Wj16tWUl5dHAQEBLtfy0ksvEQBauHDhpOs2Go1fqUX7z9LYc8KeG/Z+\namoqicViCggIoDlz5tATTzxBAGj79u1UWVlJ58+fp5///Od04sQJuvHGG2nhwoUUHBxMwcHBNH36\ndEpMTKQdO3bQjh07iMZ/0LR27VpyOByUkpJC06ZNI5PJRHa7nRYuXMi/l4iICFq6dClNnz6dbrjh\nBtq6dStt2LCBoqKiSKlU0saNG+nw4cPE7PHHH6empibat28fhYeHU1RUFKWmproUFrLfCNMY/ldr\n1zpm/qACpTt27AAwHjAtLS3FbbfdhrfffhubNm3CQw89hBtuuAGff/45KisrIZFIEBgYiJ6eHtTW\n1mLt2rX4y1/+4sLlAowr+jz99NOTzjWVcpCzTVT0mWpbs9mM7u5uF3iBlew7U8ZGRUVhYGAAly9f\nntg3ADDlEpJxm08sZGJcJn/PBOFLdShmM2fOxPDwMIKDg/HSSy9xpfTKykoXL1sqlU4i1JLJZNBq\ntWhpaeEQ0kSuc0a05rzCYf3mzCjp7F2zfnZ3d0deXh6Cg4PxwAMPQKPR8LxknU6HLVu2wN/fH/39\n/cjNzQUwnqGjUql4fjJTpZJKpdiyZQv27duHpqYm+Pn54fDhwzCZTBwe8Pb2Rm9vL1pbW6FSqRAX\nF4fDhw/z+5VIJIiKisKZM2d4MO6fyVifT+TJkclkGBsb47EbFvz28/NDeHg49u7dy5WhlixZggMH\nDiApKQkffvghLl68CJPJhJGREQwNDUGhUCA2NpZTUwcGBqKyspIfu6SkhPMDjYyMwM/PD8PDw0hK\nSoJKpUJHRwesVisKCgpw7NgxPPHEE5xQrKurC4888giH1Via79atW/Huu+9iwYIF30u/fpd2rYHS\nH9SgzjihZTIZDh06BADIz8/HkiVL8OSTT+L06dMIDw/H6OgoVCoViouLERYWhv7+fly8eBGBgYHo\n7OzkwUomZzcVHe81XPdXZsOIRCJ4enpy0V0AkwKdE/dJTk6Gt7c33nvvvUk8MxP5vb28vFBXV8f3\n37x5M5566imXfaRSKYxGI1paWrBs2TK89tpr8Pb2hlqtRnFxMR9Q2YDN+HR8fHzw6aef8sAaI9pi\nPOjs/YmiFQkJCS6BqakyDlgxkvP7KpUKQUFBuP/++7F9+3aUlpa6TJI2mw39/f3o6OjAc889h8bG\nRpw/fx4vv/wyFi5cyLm4jx07htDQUF4Nev78eRdmwU2bNpYZa+MAACAASURBVOHy5cs4fPgw+vr6\nsGLFCrzwwgsICQnhWTxDQ0OIi4tDUVER3N3dUVVVhWXLlmHXrl3w8vLi4h7vv/8+Z6hkud3/TCYW\nixEVFYWCggIA4AVirNjHOQNJJpPBbDYjMDAQWq0We/fuxZYtW3D+/HkUFxdj6dKl+Oijj9Dc3Ayb\nzQYPDw9cvHiRy9/t378fwPjz29jYiM7OTl5T0tbWhs7OTrS1tSE1NRUff/wxP+9jjz2Gjz/+GI2N\njUhLS8OFCxcQHR0NQRBw22238cA4AM7EunHjRp7d9EOzax3Uv3d45duEX5RKJV9us/bII4/wZfGc\nOXMoNDSUVqxYQYGBgRQaGkrAOBzCeCic26pVq65p2fp1rvHbaEajkfPAOJ9fr9e7wCXO7b/+67/I\n4XAQMM7X4e/vz5emmzZt4v3HoILZs2cTALrnnntclq533nknrVmzhi/XBUEgtVo9qU/Ydbi5uRG+\nWPJarVay2Wz8M2cIZ6p+Zfe2fPlyyszMJKVSSf7+/i7brVixgux2Oy1evNgFJpNKpbRkyRIaHByk\nhQsXkqenJ02bNo3i4+PJbreT3W4nQRBIKpXy5Ti7rqioKHrggQcoISGB3Nzc6JFHHqGoqCjy8/Pj\nx3Z3d+d9OW3aNPL19SWFQkE6nY50Oh3dcsstBIA8PDxoxowZnF+ENfbsfd9NKpWSl5cXf+0MBwLj\nsJdz/yQmJhIAysnJoblz5xIRUXh4OEkkErJareTr60s+Pj6k1+vJzc2N8vPzSS6Xk1wup9zcXDIa\njRQWFkZJSUmUlpZGZrOZdDqdC+QJjEOpwcHBlJiYSIsXL6ZZs2bR4sWLaeXKlfRv//ZvRETU3d1N\nBoOBDAYD5635vvvzu2zXPGZ+34P2tzmosxYXF0fp6emT3tfr9aTX6wkYJ+9hJEKMVIv9qNnAlpOT\n8406nx2HnWuqZrFYSCaTTRqkWLPZbGSxWEgQBAoLC5sSlzUajSSRSPgAD4wPlBKJZNL227dvp127\ndhHgOhFYLBa6+eabSafTuWDiW7dupdjYWLrrrrtcjqPT6Wj79u0uWCUb1NVq9aRBwWQyEQCOUycl\nJU26j4kTY3JyMq1fv57Wr19Pnp6eLp+xyVitVtOiRYs4Dm+1Wnnfs4l93bp1dPToUVqwYAGtXbuW\nIiMjKSAggNzd3cnd3Z1CQ0MpJCSE/P39eTxDIpGQwWDgpGjTp0/n1y4IAj92ZGQk768NGzYQMD5A\npqen82fP29ubDAYDmUymSfeo1WonDfTfpIWGhlJcXBy5u7uTUqkkDw+Pq/YrAB4P0Ol0fFJj2zrf\n31RNoVDw7zopKYnS09PJx8eHwsLCyM/Pj8RiMcXFxZHJZCKZTEbz58/nkwAA2rx5M4WHh9O0adPI\ny8uLQkNDSSaTkSAIlJSURHK5nPz8/CgyMpIWL15MXl5e5OXlRXfffTcB4yR9xcXFFBYWRg6Hg8LC\nwv7h/vtXaj9KTJ0tqwVBwJw5c/DOO+9wBRtmTGORLf11Oh2HC9hSWSKRwNfXF1euXPnatJpfhXNP\nZXK5nJe/M/GK3t5edHd383x1Bn309vbyZTK7J7FYDIfDgdraWoyOjmL+/Pl45513+PEZJGU2m7F6\n9WrcdNNN/Drlcjlyc3Nx6dIlVFdX4/bbb8f//d//obOzEzqdDg888AB27tzpAplYrVZs2rQJDz/8\nMKcC6OnpQWBgIMrKykBEHCdllaeMZnhkZITzkVdUVHC+G/b51fpMLpdzrngGBbDcfUYixjJxWLHY\nyMgI1qxZg8LCQqxcuRJnz55FU1MT5HI5h7mICAcOHIDZbObZNh0dHYiOjkZpaSn6+vo4tMT45Zct\nW8YhgpGREZcqYQ8PD45Ps9iI3W7nxTWMqx74EtL4Ryl8PTw8YDKZ4OXlhf7+fhQWFmJoaIiLlnyV\nkIcgjHPiTxR1YDEAnU4HsVg8KW2XxYgWL16M3t5efPjhhxCLxYiLi4NMJoNSqURNTQ1XrmIxDJFI\nhPr6egwNDaGxsZHHXMxmM9c+qKur4wVojK/cbrdznpmGhga0trbi3LlzXDuXfe8/dLtW+OUHw/0C\njIstx8TEYHh4GKdPn0ZfXx+mTZuG+Ph4pKamIjMzE0SE3NxcpKWlITo6mpcLj42N8QdjZGQEkZGR\n/EFmeeHOxFTs/Yn2TSrTWltb0draitraWtTU1KCzsxNZWVk8J5vhn4zcnw3oMpmMCyKzyth33nkH\na9as4cfWarXQarWQy+Voa2tDcnIyZyscGBhAYWEhent7ERMTg7CwMKxcuZLzvP/5z3/GqVOnkJ6e\nDmBcXCQ7O5tj821tbbzqkBEwDQ0NwWQyuXDAs2IgQRD4AC4IXwpXG41G3rcT+5nt09vbC6LxIqG6\nujpIpVIeMGW5+IzNsqOjAx4eHvjggw9w9OhRvPzyyzh+/Dh8fHxw/PhxznNitVrxwAMPcEIvxv1x\n4cIFHqjt6elBXFwcr1Gora3lFAQeHh5Qq9VwOBxcTEUqlfLiJaLxsvWamhpOVOXh4YGgoCAMDQ3h\nnnvu4fGUr2vOPP319fU4d+4cQkNDERgYCKPRCDc3Ny764Ww2mw0mk4nvO3FAZ7QNPj4+MJlMvG5A\nq9XCarVCLpcjPDwcAPDOO+/gww8/RGJiIp/I2WS7ceNGPrEwa21tBdF4KnB7ezukUinS09Oxdu1a\nHqMYHh6Gn58furq6MGPGDISEhMBms2Hv3r04ceIEqqurMTQ0xGNKjKXxujnZ9w2vfFfwC/s/JCSE\n8yAzyEUmk5GPjw9JpdJJGDRbXj777LNTHtsZ653Yrpa6NnGfrzoGvlgaq1QqUigUfHu1Wk1eXl4u\n7zPYKCUlhfLy8vj+K1eu5P8zvul169ZxbJpdK7uGqKgoqqqqooULF05afj/88MM0bdo0/nrOnDkU\nHh5OIpGIkpOTKTk5mWOurO/c3d1JKpWSVColg8HA92ec52q1mkNHzn0y1dJfEAQeC2CN4dnO52RN\nLBZTQkICx+uzs7NJIpFwmKasrIz8/PzIz8+P5s+fT3q9nqRSKYeJnHF+mUxGBoOBPD09yWg0ct5x\nuVxOYrGYbzt9+nRKSkqixMREUqvVpFarKTg4mMcTjEYjGY1G8vPzo5iYGEpISKDAwEASiUQ0bdo0\nDvV83Wa323l8Zc2aNSSVSmnWrFnk5eXFobCJ8NXfO1dCQgJFRUXxWEN8fDzJZDJKTk4mi8VCqamp\npNVqKSYmhqRSKedQZy0gIIAsFgvJ5XJKTEyk5ORkstlsZLPZyM3NjaRSKdntdnI4HBQfH0+xsbEk\nk8lo9+7dHM5xd3enX//615STk0Nubm68n+VyOUVERPB+/bG1ax0zf1Ce+nW7btftuv3o7fv2xL8L\nTx0Y90TXrFlDPj4+lJCQQGKxmHtjLJh04403XnX/iR6Oc/t7GS/OmSFftb1zAG5iwdFU2REsyMg8\nVaPRSLGxsQSMB+6WLVtGc+bMoWnTpvH3TSYTmUwm7nGy4ivWdu3aRXl5efTQQw8RAP45U/b5+c9/\nTrGxsXxVEBgYSPPnz6fMzEyeeTBV0dDs2bNJJBJx9ajs7GyXz1kw0fm+VSoV/46c+4T1k9FodPHm\nPTw8SKlUktFoJJvNRlqtlqxWKwUFBZHVaiVPT0/S6XTk6enJvTu5XE6PPvooPfroozR9+nTKz8+n\n+fPnk4+PDw987tixg4BxT10ikVB6ejr5+/vz+3Q4HNx7lEgk5HA4aO3atfwajUYjxcfHu9yrRqOh\nhIQEstvtFBMTQ6dPn6agoCCKiYlxCW5ea1u+fDkFBATQli1byGAwkF6vp/Xr11N4eDiFh4eTw+Eg\nsVj8DxU+xcfHU2pqKvn6+lJERASJRCK+Cpu4rd1up/T0dAoLC6PZs2fzFTHLmmLPDltZPf744xQb\nG0sKhYI0Gg3l5+dTXl4eKZVKmj59ustz7ty+6armh9Cuecz8vgftb2tQd17K6/V6+u1vf0sA+ODj\nXNHIIIj169e7HIPBGgAmpVh9VWOVeF/3S2KDltVqJavV6pItI5FISC6Xk1qt5j8ig8HAIQBn2Gji\nuY8cOUI7d+6kLVu2cDiAfXbHHXfw40dGRtJDDz3El8rh4eF03333UW5uLq1bt462bdtG9913H2Vn\nZ9Odd95JKSkpJJFIaOHChS7nd5aSc76v+Ph4cnNz44OsSCRyuRaWNunc5HI56fV6Pqjr9XpSq9Uk\nFotJLBbzvmbHYXBOUlISLV++nIDx9EuTyUTu7u5ksVj4QKBUKl1k7hITE+nxxx8nT09P0mq1LhMk\nuzb2PbAMo6kGGovFQjk5OSSRSCg+Pp7i4+Ppf//3f12eNWAcKsrMzKTAwECSSCTk7+/PYcCv89wo\nlUpKTk4mtVpNFouFvLy8yNvb22Uimeo6v6rid6pmNBpJoVCQSqVyecYkEsmkqkx3d3eKiYkhf39/\nioqKooSEBAoODnYZ1FkfzJgxg+Li4kgqldL9999PqampHKIzmUwUFRX1tX9LP4b2oxvU3d3dKTMz\nkzIzM0mhUNCNN97IB/rk5GS+nUajIalUSkqlknuFwGRtTabH6DxZODdnb9wZn564jfNf58YwZ61W\ny8vm7XY7qdVqPrlkZma6HFupVLrk4mq1Wp47DYxPZjqdjrZu3UoPPfQQ+fr68s/YcSb+sNetW0f5\n+fm0fv162r59O4WEhNBPf/pT2rZtGyUkJHAKhMjISPLz8yMi4ql47B4cDgf3yhQKBd9HKpVSREQE\neXp6kkqlIplMRu7u7tzrdx6EnPuJeZhsIHHuPxYHcZ5UBEGgdevWkd1uJ6VSSWq12uU79/Hx4bqX\nE7+H7OxsCgkJofT0dDIajbRo0SK+qnEekFlj965SqSg8PJzS0tLI4XBQRkYG/46USiUFBASQTqej\nt956i++rUCho2bJlBIxPBCy9kLVrqYuY2Dw8PCgnJ4eys7M5rQHwpZan87m/60GHrXBYY6sqRtuQ\nkZFBQUFBZDQaSaVS0datWyksLIzmzJlDRqORkpKSyGAwkFqtnjQZXG/XPqj/YDD1pqYmeHl5wcvL\nC1lZWfjggw8wMjICkUjE1eXXrFnDBQ+AL8mEWCojM41GwyvqJmYHMPtiwuH/O7+euM1UnzFRAibk\nMDY2xlMDh4aGYDab8cknnyA7O5vv39/fD98v1N6B8bRGlsYplUqRkpLCldEffvhhTl7ESvKB8YyX\nwMBA/OpXv4LJZEJQUBA6OzuRk5ODI0eO8Iygixcv4tSpUzyb4fz58zwV1MPDAzKZjFcFEo1rg3Z3\nd2NgYAANDQ1QqVQQBAFBQUGor6+HwWCAw+FAS0sL2tvbkZSUBJPJhIiIiEn9xfqDycs5Z3DIZDIQ\njQuRSCQSeHt7QxAE/OUvf0F9fT1UKhU2b96MgoICREVFwWAwoKmpCf39/ejp6XHJNhEEAYcOHYLZ\nbIZEIsGsWbN4imF8fDzKy8shlUq5wEdYWBi0Wi2mT5+OzMxMzJgxAydPnkRLSwvnGo+OjkZ0dDTK\nysoQHh6OxYsX4/bbb0dkZCRGRka4ck9zczPKy8thtVqh0WiQkJDASee+jnV0dKCiogIjIyOoqalB\nVlYWfHx8oFKpXLZjxG/flYlEItxxxx3IyMjgMor9/f0IDQ2FyWSCyWTC0aNH0djYyEUyfv/730Ms\nFuPIkSOcFrm9vZ2n9F63b2Y/mEEdGKdOzcnJwalTp3DzzTdj1apVeOGFF/DSSy9BJpPhr3/9K5en\nCw0N5dwjIyMjsNlskMvl8PHxQXd3N06fPs0fzqmMpS5ebUD/OsYGAr1eD6JxLveWlhaIxWKcO3cO\nS5Ys4efcv38/tm7dio0bN6Knpwfd3d2QSCTIzs7m/CLOTI3s+pyvt7y8HOfOnUNraysCAwOxadMm\nvP3226irq0NbWxvi4+NRW1uLhIQEdHZ2co6XoaEh+Pr6wsvLi+egy+VymEwmnoLJ1G1YjvObb76J\n6upq+Pj4oLm5mQ+qp06dcqHkBYC4uDjeByw9kUkIAsA999zDuUkYPwmTK3R3d0dycjKWLVuGW2+9\nFV5eXkhOTkZRURHkcjm0Wi1P1XTum4GBAZSUlCAjIwO5ubm4fPkyQkJC8Pbbb8PDwwMqlQpE41TA\n3d3dKC4uRm9vL86cOYP29nbI5XLIZDKeV+2cktnb2wuDwYBnnnkGpaWlyMvLw8GDB/m1BAcHQy6X\nIygoCLW1tZBKpZx18FptYGAApaWl+OSTT1BUVISLFy+ipqYG586dw9jYGJRKJSIjI+Ht7c378bsw\ndk8HDx7kqaoAcPnyZTQ2NqKxsZHrwo6MjCAsLAw+Pj7o7e2FRqPByMjIJCGU6/YN7fuGV74t+EUQ\nBAoJCaGQkBCaPn06WSwWys7OpsDAQL5NcnIyrV69mmbPnk1qtZpMJhOJxWKXlD1nyIT9P5EZELh6\n+uLXaV8VcHWGHjw9PXkFpzOL409/+lOSSqWUn59PWVlZLvtPxDxZeTYA8vPzo7/+9a8EjMcOtmzZ\nQjNmzKCwsDC6//77J8ECOp2OL6Xd3NzIYDCQv78/aTQa0mg0NGfOHBecleHrjKEwPDycIiIiOCTA\n2CPVajWHI6a6ZgAuaZ0TP2PXxPomKyuLsrKyaM6cOS7wS1xcHAUEBPBjMDhg06ZNLuecMWMGRUVF\nkcPhILVazSuKxWIxabVaXk7PAtarV68mALxiNC0tjebPn0/z58+n5cuXk7+/PxkMBnI4HKRSqWjL\nli304IMPTrrXnTt3UkREBIf8vmnz8fEhiURCYWFhHJ5yTnX9rp7Vqb6Tq7WEhAT+HH1djP/H3n50\n8AsR8UKbo0eP4o477sCHH37I+a0NBgO6urrwyiuvoKamBunp6bxg5/jx4y5CFex4RISUlJRJSj/f\npMDoatcMjBNdJSQk8CWy0Wh0qYKtq6uD2WyG0WhEYmIiPD09AQDl5eVc9osVhEw8NlsFtLW1weFw\nAAAaGxuxZs0a/Pu//zv++7//GzKZDAkJCZy1sqysjGt0MnjHWU4vOTkZ5eXlkEgkkEgknJ1waGiI\ne7ZDQ0Noa2vjSvA9PT0gIsjlcq4PajKZMDw8jPT0dDz99NMYGhriqwJmTKhYKpUCgMv/rPq3oaEB\nwDjEcODAAZw9e9aFw72oqIiz9jFPcWRkBBkZGRgaGoJOp+PMf+fOneNc+4x4ymAwQKfToaGhwYWU\nbPfu3YiMjITNZkNkZCRuuukmFBQUcJm78vJyrpubn5+P8+fP46WXXkJERATvC5VKhSNHjuDChQs4\ndeoUpk+f/k0eJQBAVVUVRkZGcOnSJV74tXfv3im3FQQB+fn5LgLh/6gtW7bMRXSGWXx8POLj43H3\n3Xfzvuvp6fmn0f78wdn37Yl/W546gEmZHmFhYS5epiAILlziDoeDew5Ttat5JxMLib7ONbJmNpvJ\nz8+PbrnlFp526EyExXhf2PZxcXFktVp5Fg/jOsnOzqaNGzfSTTfdRIBrQCw9PZ2YiUQi/v97771H\nY2NjtGHDBjp69CiFhITQT37yE7rhhhvo3nvvJZVKxYOZdrudZ2doNBoSiUT03HPPkY+PD3l6epKn\npycv9rLb7aTRaMjX15dsNhsn8RKJRDRjxgzauHEjqVQqHuxl3upNN91EERERpFarXYK7wGSueufA\ntEwm4wFuRkrGjimVSl2CymazmRYsWEDR0dEUGxtLsbGxpNVqKTMzk0JDQ0ksFlNMTAzdcccdJJPJ\nXDKRsrOzKSgoiLy8vCg6OppkMhlfSYWFhdENN9xA3t7etHDhQl7sxTJ2tm3bRkFBQSSVSik6OprU\najVP72THYfcsl8vpt7/97VcSnV1vP972o/PUASArKwtZWVkAgIULF8JisUChUEAsFiMxMRFGoxGD\ng4N46aWXsGrVKjQ3N3PPgZX8MxydBRgnUgFMfK1QKBASEsJf22y2Ka+N7WexWCAWi9Hb24uKigq8\n+uqrnCZAJBJxqlp/f3+X1QArV3/jjTcgCAIaGxsxc+ZMlJWVITMzEy+++CKkUikGBgbw4IMPQq1W\n47PPPuP7j46O4pVXXsHJkyeRkZGBjRs34tFHH+V6rsHBwdi1axcGBwfx/PPPIysrC1KpFI2NjZBI\nJBw7njVrFn7+85/j//2//4e6ujrU1dXhzJkzCA0NhUgkQnd3NyorK3lZfFBQEKdgKCwsRHh4OAYG\nBiCXyzF79mzEx8fj8uXLuHDhAnp7e1FZWemCK5eXlyMjI4OvHJy5dcbGxjiGXVlZiVWrVnF6gpGR\nEa5uD4x7/AUFBRgcHMS2bduwbds2DAwMoKqqCq2trbDb7SgsLMTBgwcxNDSEoKAgCIKAlJQUVFVV\nQalUQqlUckqJsbExJCcn49KlSxCLxaiurkZWVhbi4uIQFxeHt956i3PQ6HQ6OBwOyOVymM1mHDly\nBBKJhK8S2AoqISEBL774In993a7bN7Lv2xP/tjx1Zw81IiKCDAYDzZo1i4KCgngq2x133EEZGRk8\n/xkYx649PT3p2Wef5QpDwLgXdbWy9am8c09PT0pKSpq0D7suVmQxcV+RSEQWi4UsFgspFAruaUok\nkkkUBiKRyIX1DhinBGCFQjqdjhwOB23bto2AcQa/y5cv0+XLlykpKYnmz59PMpmMaLxjyWw288KX\niTnjS5YscWGQZN56ZGQk///mm2+mm2++mcRiMWk0Go7lGgwGvg0rJGGFK4xxj7XAwMBJfWa1Wl1o\nfaOjo/kxJvY7K2dnVBDOTSwWu6zc5HI52Ww2ioiIoIiICNLr9eTv78/ZCh0OBy1btow8PDwoMjKS\nNmzYQHfeeSfPUX/11VfpmWee4TQOmZmZ/D4zMjIoJCSEEhISKCEhgWJiYigmJoaio6M5Ru/n50cO\nh4MefPBBslqtpNVq6d577yVvb29SqVRksVgoJCSE7HY7BQUFfa9pfd/GavR6+3bbtY6ZPyiWRqvV\nCmDcG87KysJbb70FlUqFixcvIjMzE83Nzbhw4QLHxJkn7jSBAABnRATGUwUtFosLmx7DhNkxALjs\nHxsby8UHYmNjcenSJQwODsJoNKKtrW0SJq/VagGM6zSWl5dzHVRnz12j0bhkbrBjrFu3josjd3d3\nIzExEffffz9CQ0Ph5uaGvLw8AMCFCxfw3HPPYevWrVzQQiQSQalUYmRkBG5ublCpVGhoaMDIyAgX\n1UhISOAq7UFBQVx9SRAE7j0nJSWhtbUVkZGROHToEJqamjirYkhICGJjY/Hqq69iwYIFUCqV2Llz\nJ3Q6HYKDg+FwOPDGG29g3bp1eP755yfdN2NJFAQBJpMJLS0tLn3BvPLQ0FCUl5dDLBajv7/fZT+t\nVgtPT09UV1fD29ub6422tbXB398fDQ0NGB4e5gpKTFw8MTERIyMjKCoqgkgkQlNTE+x2O2w2Gy5c\nuICcnBy0traipqYGKpUK6enpPEUzLy8Pt9xyCzo7O2G1WnH27FnEx8ejuLgYZ86cgVarhd1u5+IZ\nM2fORE9PD0pLS6FSqSAWi+Hr64vDhw9PEkS5bj9Oo2+LpVEQhABBEP5LEITPv2jFgiB8KgjC/Anb\nuQmC8N+CIBQJgnBBEIQPBEEIn+J4UkEQHhEE4ZIgCOcEQTgsCELatd/a1a2vrw99fX3w9/fn0nZ6\nvR4xMTEQiUQoLS1FZmYm3N3dYbfb+RLe09MTBoMBIpEIer0evb29nF1ueHh40oDOpOHYpDCRCY8p\n3gBAQUEBYmNjYbVa0dbWBsB1AgCArq4unqfb0tLCr02r1XKB3eHhYfj7+/PAJQsKazQaPP3003j1\n1Vexfft29Pb2Ii4uDlFRUZwhsKamBmFhYXjrrbcQGBiIX/ziF/j1r38No9HI2Q/Z4HTfffdh27Zt\neOaZZyAWi6HRaFBbWwuRSIQrV65w5SO5XM4DYAMDA+ju7sbrr78OAFy5iLHt7d69m6cbHjx4kFOq\nFhUVwdvbG1KpFEVFRbxvRkdH4eHhAQ8PD15TEBoaivb2dlitVi73B4zXEchkMhQVFeFPf/oT+vv7\n4ebmxgd0YFxR6vLly1wBieXXa7ValJeX49577+X1CENDQxCJRIiIiEBdXR3Gxsbg7+/P6xhKSkrw\n8ccfo7e3F+fPn0dhYSHEYjF6enrw+uuvIygoCEFBQbjjjjtgNpsxNjaG3bt3QxAEvPLKKygvL+fp\nmlVVVRgaGkJ6ejqvJRgcHERISAji4+Oxb9++6wP6dfvadi2Y+jwAKwGsIKJEAKEADgHYIwjCTKft\nXgcQDSCWiCIAHAfwiSAI9gnHewrAcgAziCgKwP8C2CcIQsw/divAvHnzMG/ePK4o7u/vD6PRiKam\nJlgsFthsNmg0GgQEBPCB2mq1ora2lkfiOzo6IBKJOA81w2SZZ+uclcImBZbvzqypqYnLpjkcDhw/\nfpzvx7JUVCoV/5xZa2srHA4HRCIRUlJSIBKJUFZWhsHBQSgUCvT19SEjIwPz589Hd3c3zGYzFi9e\njLvuugtPPvkkhoaGsGvXLmzYsAFHjhzBwYMHkZ2djezsbKxbtw7d3d2IjY1FXl4e3nvvPR5/ePfd\ndwGMc68/9thj6OnpgUqlglqtxqlTp6BQKDA2NsZzxquqqpCeno7S0lKUlpaiuroaer0enp6eiIuL\n45NdRUUFrly5Ap1OB6lUiqeffho+Pj4YGBiARCJBZGQkXnnlFQwNDeHkyZOQy+XQaDTQ6/V8gg4O\nDgYArmcJjA/kUVFR8Pf3h81m432/efNmLFiwgE/IRASRSARfX1+YTCb4+/tjbGwMxcXFKC4u5pka\nv/rVr5CSkgIiglqtRl9fH89vj46OxpEjRzA6OgpBEBAZGQk/Pz/MnTsXIpEIAwMD8PX1xaJFi6DX\n63H8+HEcP34c8+bNw5EjRxAbGwuz2YyioiIkJiZCLBbjpptuQnJyMtzc3KDX6zEwMICamhq88sor\niIkZ/xnU1dXhxhtvhFqtnpLi+bpdt6vaNWDaSwD8WX8yeQAAIABJREFUdMJ7OgBjAP7ri9c5X7zO\ndNpGCqAVwH87vRcCYBTA+gnHOw9g7z+CqYtEIqqsrKTKykrKzs6m3/3ud5SUlERLly4lwBUztlqt\nlJaWRhkZGSSVSikyMpLEYjFZrVayWCyT8mevhimGhITwLBFnygC73U42m43zbwQEBJBMJuNZDlar\nlQwGA0kkEhfc1GAwTMKXGV7ufA1//OMfKT09neLj4zkFKjvu+vXr6Z577qGoqCiyWq20fft22r59\nO2m1Ws7p0traSn5+fiQSieixxx6jiIgIAkDR0dG0ePFi3lcsw2bdunUu16jX610UjP7jP/6D7HY7\nZWVl8Vz4+Ph4XhIOjOfGe3t7c3zZZDLR2rVrSSwWk0wm46pDTDmJ0QT4+vqSTCYjk8lERqORxGIx\n1dTU8HOz7Bh2XGA8916lUrnEH5wJ0lQqFalUKpcMF0EQKC8vj/R6PWm1Wlq6dClFRkbSrFmzKCIi\ngqRSKf3sZz+jNWvWUGBgIKlUKtJoNOTl5UW5ubmUkZFBK1eupNzcXMrNzSWr1UpPPvkkAaBbb72V\n1qxZQ6mpqbRhwwbS6XS0atUquvfeeyknJ4c2bNjA+WDmzp1LK1asoPz8fN7/19v1BnzHmLogCN4A\nKgH8nIh+KwjCHwGsB+BGRCNO2+0BkEREti9ePwDg1wD8iKjKabunAGwCoCcil+TVa8XUo6KicOut\ntwIYL///61//CrvdjpaWFiiVSq4Iw8rX/fz8UFVVBSJCT08PYmJiUF1dzavaJnrlf6c/XErxbTYb\nGhoaMHPmTBw7dgyjo6OIj4/HyZMnuecfFRWFoqIiDA0N8f36+/vh5eXFKysvXbqEsbExnD59GgAQ\nGRmJ8+fP4/Tp09i8eTPPD2eK7wCwdOlS7N+/H35+frhw4QLMZjOAcVWl+fPnY/HixXjhhRegUqlQ\nV1eHkpISqFQqnDt3Dvn5+di7dy8SEhIgFov58ZkYhUqlgkwmQ2BgIIqLizFr1iwAwJ49e5CVlYXK\nyko0NzcjOjoahw4dQmhoKIqKiqDRaODl5QW9Xo/y8nJ4enri9OnTWLp0KY4ePYqwsDB8/PHHEAQB\nCQkJKCgo4LCLWq3GtGnTcOrUKXR2diI3Nxf79+/n8JfBYIBSqURdXR3UajUGBgawfv16fPjhh6iq\nqoLNZoNYLEZtbS3i4+Nx5swZnqFUX18PtVqN/v5++Pj4cDUmJqARFRWF/fv3Izo6GpWVlXylYLfb\nodPpQEQwm804e/YsLBYLysvL+TaBgYGQy+UYGRnB4cOHkZqaipaWFqjValy+fBnu7u6YNm0aDh8+\nDIvFgp6eHrS0tCAiIgJVVVUoKSn5Ws/gdfvh27eGqU80QRA8ATwN4NQXf4Fx2KXeeUD/wioBWAVB\nMDttNwpgorR6BQAJgEkY/LWaVqvlSjwHDx6E3W5HfX09FAqFC6eGl5cXVCoVSkpKMDg4CCKCwWBA\nYWHhpBJyp3ue8pwajQZKpZLDMMy6urogk8lQW1vLy+lPnjwJmUyGnp4eDA4O4ujRowgICEBvby/6\n+/u5qn1DQwPefvttvPjii1i/fj2efvppXmxz/vx5AMD27dtBRJgxYwbHupcuXQpgPGjZ19eH8vJy\n3HbbbbxEu6qqCqdOncJTTz2FsbExXLp0CSaTCXq9HkFBQbDZbFiwYAESEhLQ3d2Nw4cPQxAEeHp6\nYmBgACaTCWq1Gh0dHTAajeju7saePXuwZ88ehIWFAQDS09Px/vvvo6GhAf7+/pBKpYiNjYXFYkFZ\nWRlGR0dhMplw+vRp+Pn5ob6+Hi0tLaioqOB9WFlZCZFIxGMG06ZN4+r2giBg3759WLduHcRiMYdX\nGD9Nb28vXnzxRT6ge3l5QSQSoba2FgBw+vRpJCcnIzIyEpGRkfw7jImJQW1tLZc/VKvVkMvlOHTo\nEH75y19Cp9Px9EwvLy+Eh4ejoKAA9fX1OH78ODw8PCAWi9HS0oIZM2ZgxowZMBqNMBgM8PT05JNm\neHg4ent7kZeXh5GREXz88ceor69HRUUFkpOT4evri48//hienp645557vulP4br9yO2aB/UvAqal\nAGoACADyiYgJeJoBTMXA0/XFX5PTdn00eXkwcbuvbU888QQ6OzvR2dnJBw9WCZqWlgaHwwGtVouS\nkhJeQalUKqHX69Hf38/1QZmxS/yq6tGhoSEXXVRg3MOXSCRQKBT8/CEhIXxAiIiI4Bwc8fHxsFqt\nLvnwDLuVyWT42c9+hjvvvBMikYjnz+t0OuzduxdHjhyB1Wrlk0lraytiYmIglUqRkJAAX19fHDt2\njF/rpk2bcNNNN0EqleLEiRPo6urC0aNHsWXLFqxduxY+Pj745S9/iYSEBFy4cAEOhwN6vR51dXXw\n9vbG6Ogov5/e3l6Xys+SkhJ0dHTgL3/5C/bs2QOZTIbp06ejq6sL1dXVqKysBDC+Wrhy5QqsVita\nWlpw7Ngx6PV6tLW1Yfny5QDGg5pSqZRLzn300UcoLi7G8PAwDx4///zznEPG398fqamp0Gg08PPz\nw86dOyGXy5GRkYHa2lrU1dVh0aJF/HtqbGxEWVkZysrKYLVaceXKFZw5cwaZmZk8O4dNGO+++y52\n7NiB9vZ2CIKAnp4eREVF4ezZszhz5gz6+/uxYsUKnDt3DmVlZQgICEBTUxOamppw7NgxzJs3D088\n8QQUCgV0Oh2ampoglUpRV1fH4wUJCQmYNm0a13dlq4jHH3/8upd+3b6RXfOgTkRlRBSIcTz9MoDC\nbytr5R81b29v3HDDDaivr0d9fT0++eQT7N+/H93d3Th16hROnjyJsrIydHWNzx11dXU4evQojEYj\nXy6bzWaeaeA8uH+VDQ4OciZEZmNjY+js7ERXVxdWrVoFYDwtkjHptba2QqPRYOnSpfjzn//MNSCd\nUySJCElJSRAEAadPn8a8efMwMDAAkUiEzs5OF7iGBdYUCgX0ej3uu+8+SCQS+Pj4wGq1Ij8/H/n5\n+fjjH/+Io0ePYnR0lA9EKpUK7733Ho4dO4bS0lK8+OKL+PTTT5GUlISamhoORel0OnR0dPB7FAQB\ntbW1XBN2dHQUFRUVSEtL4/dUUFDAA79msxlqtRptbW0YHR1FXFwcuru78cILL6CrqwshISEwm824\n8cYbMTo6ygO1LJisUCi4LurQ0BAUCgV6e3shCALOnj2Lzz//HMHBwUhOTsbu3bsRGxsLd3d3CIKA\n7Oxs7NmzB319fdBqtaisrERKSgpSUlKg1WqhVqsxc+ZMnrGjVqsxPDyMZ555Bu7u7li/fj1uu+02\nBAYG4uzZs2hoaOBB4eDgYOzZswdarRaBgYGIi4vjE8bPfvYzrF+/HmazGb/61a8gCAJKS0thMplQ\nX1+PoKAg7N+/HxKJBAUFBWhvb0dlZSV0Oh0Xtr5u1+0b2T9QFHQRQOEX/x8BUD7FNn/AeADV/MXr\nlwGMAONYvtN293yxXeI3CZQyTU6ZTEYymYyCg4N5wI01q9VKixcvppiYGC7a4FyYMhXX9leRdslk\nMl5eDkwdTA0JCSFgnOfcufT7D3/4AwHjfOjOog1btmwhALR161YXNZzZs2eTXC6fVJDE/n/44Ycp\nLi6OfHx8aNmyZfTaa69Nec0//elPKTo6mutKxsbGUmRkJKcISE1NpeTkZB5gZIVGjCt8xowZpNPp\nePCWNYPBwDnNgXE6AYfDQVarlXQ6HW3evJkiIyMpIiKCli1bRgaDgYKCgsjT05PsdjvvJ19fX4qK\niiI/Pz9yc3MjNzc30mq1LsFodk7ngDJ7nxVLhYWF0cqVKzl9wfLly0mr1ZJCoSCHw8E1M+fOnUvz\n5s2j3NxcUigU9Nxzz1F+fj49+OCD5HA4uDqTQqGgnJwcMpvNJBaLadasWbR06VKaPXs2ZWVl0axZ\ns8hqtVJVVRWlpKRQSkoKv7bw8HDKysqiuLg4+uSTTyg5OZm2bt3K+3fBggW0YMECmjt3Luf3v050\ndb1N1a51bL6WPPWr8c+eBxAhCIIMwFkAnoIgSCZs4wfgChG1fPG6EOOrg4l10H4AhjE+UXxtq6io\nwIoVKzA0NMQb88qZdXR04K233gIwHkiVyWRYuHAhoqOjERUVhZ6enknHZR7x1TD13t5ezvk9cTtB\nEFBWVgZBEBAaGurCy/7AAw9ALBajq6sL9fX1HH558sknMX36dGi1WmRnZyM+Ph6/+c1v8NFHH2Fw\ncBCjo6Mu52OY8sWLF9HR0YGBgQEMDAzgjTfemHStqampaGhowOrVqzEwMIDk5GQ0NjZiaGgIPj4+\nGBoagp+fHy5fvozPP/8cwDgUNDw8jLi4OLi7u+PQoUPIzc1FVdV4jNvb2xve3t4YHByEWCzGCy+8\ngCVLlqC7uxs2mw1eXl7o7OzEjh07eGBxYGAAq1evRmNjI9577z0YjUYUFxcjICAAYrEYlZWVICIe\nZ2D894888giAL2kcJBIJZDIZTCYTdDodbrnlFvzkJz9BRkYGampqoFAoMDw8jNTUVLzzzjvw8PCA\nVCqFTCbjlMEeHh5ITU1Fa2srbr75Zhw7dgxVVVXYtWsXbDYbEhMTed8dOXKEFyi5ublh9+7d+Oij\njyAWizE2NsZXR4w6obKyEr/5zW9w8eJFbNu2DZs3b8bly5fR2dmJN998E0T0/7F35vFRV/f6f8+S\n2TJrJpOZZDJZJglZICuQBSOrAgIiyFJaqlZrrXXv5f6s7e1ibeu9tS1tra3e3nq9VtFqRWRRRFRk\nEUyAEPYlkJA9Idtkz0wmOb8/0jkFxF7aul2d5/U6LxIyM98z30k+3/N9zvN5HpYsWUJvby/Jyck0\nNjbS0dGBy+WSd49hhPGP4HLol9cVCkXxJf4/CegRQgSAlxmTMEo65i/F/gpg7XnPWcfYVWfGRa81\nA3jjYuXL5aK8vJw33nhDfh/icM/H97//fZRKJRqNhszMTKxWK3/60584dOgQhw8fvuTrnt8terEP\nTCAQoL6+HqPRyMjIyPu6UkNfm0wmqqqqpJZd8Rfv7/P/cEMaeJ1Ox549e3jvvfd48cUXOXbsGN//\n/velYgbGqJzzudaSkhKqq6vp6Oigr68Pl8sFwK233soDDzwgH5ednU1sbCy//vWvZVDFxIkT8Xg8\nUmXjdDoxGo3yfYaone3bt3Pu3DlmzZrFunXr5MZoiO4SQhAMBlEoFLzyyiskJiZy8uRJYmNjcTgc\nxMXF0dbWJhuZTCYTaWlpLF68mPT0dKZNmyYbm0wmE11dXbjdbtxuNxaLBaVSyfPPP48QAoPBgM1m\nY2BggMTERDo7O/H5fOzcuRO/38+OHTuYMmUKL7/8MoODg9TW1mKz2Whvb8ftdlNfX09hYSGFhYWy\niMfFxXHs2DE2btyI2+1Gr9dTV1fHL3/5SwDefvttBgcH6e7uBsYa0kKOmtu2baO7u1tebBITE0lM\nTCQpKQmFQsGaNWtwu91s2LCBCRMmMHnyZPR6Pd///vdZs2YN+/bt46WXXmJ4eFieB7/fL5VFYYTx\nd+MyaJZtwBYg6i/fK4B7GKNLHjzvcZuBHYD+L9//EGgFYi96vceBE4D9L9/fDPQDOf+MTv1S4+qr\nrxZ5eXkiOjpa2Gw2MW/ePOF2u8WUKVPEVVdd9T4HQLjQ2+VyPC+8Xq/0bL84ozPkw32p56lUqku6\n8U2ZMkVYLBYZ7WU0Gt/nAROimQCxcuVKAWN+6StXrhQ/+MEPRG5urnjmmWeEx+ORz4mKihK/+tWv\nxOzZswX8lb4IuQwC4hvf+IaYP3++MBgMQqfTieTkZBEdHS0yMjKE3W4XeXl50ivnUu/nfLpq2rRp\nori4WMydO1fSHitWrJCa+BBFFDr2kiVLRHR0tFAqle/LqJw6darIzs4WcXFxwmazyRg8s9ks3G63\nuPnmm0VkZKTQ6/XCZrOJK6+8UixatEj8+Mc/FldeeaUoLCwUS5YsEQaDQXzlK18RcXFxIi4uTmRm\nZoovfvGLYtq0acJoNAq73S5uuukmkZOTIx5++GExb948cccdd4jrr79eTJs2TSxdulRmkEZEREiv\nH4VCIbRarVAoFCIpKUkkJSWJRYsWCUB0dXWJ+Ph4IYQQmzZtks6Rs2fPFqtXrxbz5s0TJpNJZGVl\nSU3/xIkT/6Ew6vD4bI/LpV8upksuhX8DbgW2KxSKIKAD2oGVQojnz3vcUuCnQKVCoRhhTCUzXQjR\nfNHr3Q38AHhXoVAMM6Z8mS2EOHQZcwkjjDDCCONv4DNl6BXSc4caV2AsAs3n87FmzRpiY2O5+uqr\neeqppyQ3arPZpKnSBxxfctfA+2RmOp0Oj8dDVVXVBUZh8FcrgFBjUOjnERERkrKJjIx8H59fXFyM\nWq3mC1/4AnfffTdms5menh5mzJjBu+++S15eHocOHWL8+PF0dnZSW1tLaWkpxcXFrF27liuuuILR\n0VH27dsnPVUAVq5cSTAYZMaMGWzfvp3y8nL8fj/Tp0/n2LGx7Qy32825c+coKyujqKiIvXv3ygCR\nuXPnsnHjRn73u9+xYcMGtmzZAiClhufvY+j1eqkoiY6OxuVycffdd/PQQw/JqLtnn32W/v5+jh07\nxpYtW/D5fBw7doycnBx27NgBQG9vL7NmzeK9997D6/XS0dEhAzACgQC1tbXY7XZ6enoYHh7G4XAw\nbtw49Ho927dvJyoqivb2diwWC0VFRRw7doylS5cCY7a+zc3NpKWlUVdXR2RkJNu3byc7O5sVK1aw\nceNGent78Xq9+Hw+3n77bVasWEFVVRXt7e0kJCTQ1NTEwMAAtbW1FBUVSZOzkB3ExIkTueWWW7j3\n3ntZsmQJdXV1nDt3jmeeeUbuYzQ1NUl76P/8z/9EpVJRWFjI7t27/5ff+DA+T7jc5qPPVFG/GC6X\ni8TERM6ePUtrayuPPvooTz/9NJWVlVJPfn5H58UNR+dLDC/lxngxzndvVKlU0pgqVNRDiI+PlyZZ\nycnJnDlzBhi7QITmE3J0NBqNmEwmmpubyc/PJzIykuLiYl588UXq6uq46667eOyxx5gxYwYmk4ms\nrCzi4+NJTEzk0KFD/Nu//Zs8bn5+Pna7HYfDgdVqZfv27dx0001s3ryZ+vp6WltbKSgooLy8XG6S\narVa/H4/FouFnp4e4uPjGR4epqWlhZycHGCsOIbOZ2dnJzExMcyYMYMXXniB7Oxszp49y7PPPssX\nvvAFioqKOH36NDfccAO9vb389re/RaFQYDQaKSoqora2lvT0dJnY4/F48Pl8ZGZmsn//foqKijh5\n8iTJyclyQzeEGTNmMH78eM6dO8fZs2c5fvw40dHR1NTU4HA48Hg8dHd3S1fMhoYG2tvbZYD1mTNn\nZEfniy++yDXXXINCoZCmY6H81K997Ws8+uijJCQkEBcXxx//+EdGRkZISkri3LlzAJSWljI0NEQw\nGKS4uJhf/OIX/OY3v6Grqwufz8fq1au54447sNlsBAIBBgcHaWpq4t1332VgYOCSG/dhfL5xuUVd\n9eCDD37EU/nn8MMf/vDBf/S5dXV1lJaW8uyzzzIwMEBdXR3f+ta3eO211/D7/XLj8vxNS6PRSCAQ\nuMCWF/66aXqxEmbZsmVylQt/Lfqh1X2oSzW02gVka/ro6OgFYbs6nU66AYbMpiIjI0lNTaWhoYHm\n5macTid33XUXarVa6t/9fj8RERGYzWbOnDnD2bNnSU1N5Yknnrggim/hwoXShKqyspK9e/cyceJE\nHnzwQXJycjhy5AgajUYWppycHBobG4mIiCAlJQWHw0Fvby8DAwMEAgEWLFiA2+2mrKyMqKgo2tra\niImJISoqioqKCmJjY2UYdlJSErt378bn89Ha2squXbsoLy9n7969VFVVEQwG5cUtEAgwb948cnNz\nmTJlCseOHePkyZMsX74cn8/HqVOneOihh+jt7UWr1TIyMoJOp5PHHR0dJSUlhfz8fIqKihg/fjwW\niwWj0Sjfe0tLCxkZGXKDs7+/H7vdzrRp00hPT0cIwYIFC/j+97/PgQMH0Gg0DA8PU1dXx4EDB7j6\n6qvZsmULnZ2d+P1+abEcCAQYHh4mKSkJnU7HhAkT+O///m+io6O57bbbsNvtbNy4kY0bN1JeXk5+\nfj59fX0cOHCAmTNnSu192MQrjIvx4IMP/vByHveZXanHxMSwbt06xo8fL538xo0bR2RkJEePHpXN\nNCqVinHjxnH8+HH53JDnhlKpxGAw0NfX94ErdY1GIz28/zLf9z3m4lX/+Qil4cBYU9Ty5ct59dVX\n6e/vx2g00tfXx5IlS6isrCQ9PZ0//OEPLFiwgEAgQHNzMwsXLmTnzp3MnDmT/fv3U1xcTFJSEtOn\nT2fy5MnvOy/Tpk3j29/+NnPmzGHlypVs2LCBW265hUcffZSMjAxsNpt0lSwoKODs2bP09PRgMpku\naHyyWCzSDRHGqC8hBBMmTGDfvn1SSqjVapk7dy67d+9+X9brFVdcIf1lLsb9998PQHNzM88884zM\n87zppps4ffo027dvx2AwEBERQWdnJ9/4xjeoqqpiw4YNCCG4+uqr5YUi5BEfQigH1Gq1So8ev99P\nWVkZWq2WsrIyvvOd73Do0CE2bdrEq6++ys0330xCQgL79u1j2rRp2O12eaezevVqxo0bR2lpqWwc\n8ng89Pf3s3LlSoQQREVFkZ2dTVJSElu3bsVms/Hzn/8clUpFWloaZWVlF9hZhBHGxfjc0y833XQT\nOp2OKVOmsGHDBmw2G+vXrycmJoahoSHp4R0KWQgV8vMLb6hd/Hxr3dAKPFTcjEYjwWCQoaEh+Vyj\n0YharZYXjvNpmfMRomgmTpwIQHt7Ow0NDZSUlLBr1y4plwx1i6rVak6ePMnKlSt58803GRoaAsbu\nFvbt28e9997LunXrUCqVLFq0iFtuueV952X58uXSICs6Opre3l6Gh4fp6upi27ZtxMXF0dDQwNDQ\nECUlJZw5c0au3LVarTT3CskLASmlbG9vZ2hoiLy8PJqbm+np6SEiIoKenp4Lgkf+HoQK8J49e1iw\nYAEZGRn84Q9/kOfWZrPh9/t5+OGH2bBhA7t37+btt99Gp9Px2GOP8ac//Qm9Xi87d+HSey+hz2jc\nuHGS2hkcHCQmJobGxkamT5/O4OAgLS0tVFVVMXnyZPx+P4ODg2RmZhIIBDh69ChxcWNO01lZWbz0\n0kukpKSwfPlySkpKeP755zly5AhPPPEEP/jBD4iKiuLJJ5/E4XDQ1tYm92BaW1v/7vMUxmcfn/ui\nfs899xAREcFNN93EihUr6O7uxmq1otVqUavVHDt2TDYqhYIuQgU8hFABAz5wo9TlctHW1sbIyAgR\nEREMDw9/4GoduIDOEUKQnZ19gU7e4XAghKC9vV1ePEKPufHGGyU/X1NTg1ar5ciRI6SkpBAdHc3b\nb79NRUUF99xzD2azme3bt1/y3IQSjKZOnUp8fDyjo6Ps3LmToqIiNmzYgNFoxOl00tzcjBBCUhMh\nr5y6ujoUCoWkjkK8+7/8y7+wevVqEhMT5QXp5MmT3Hbbbbz00kt0dHRc9uc3deqYVf+OHTswm80E\nAgGioqIYGhoiEAjIpqSsrCwSExMZGBhgcHAQh8OB3W6noaGBCRMmcOLECa677jqampr4yU9+8r7j\nqFQq9Ho9ERER2O12XC4X+/fvx+Px0N7ejsvloqenh46ODlnk29ra0Gq15ObmUlNTQ0xMjAwEOXr0\nKABtbW0sWrSI7373u/zkJz/h+PHj6HQ6YmJieO2112TzU0pKisySTU5Opq6uLtx8FMYlcblF/TMV\nPH0+bDabbH6xWCxyBVRRUSFXkAaDQRbzkBoFICoqiujoaLkR+LfQ0tLC6OgoJpOJ4eFh1Gr1Bc1K\nCoVCGlSFXn/u3LmSE7+48amzs5OoqCgKCgoYHR1Fp9NJn5YXX3yRxMREgsEgIyMjdHZ2kpmZyb33\n3ktycjL33nsvTz75JAcOHKCoqOiS83U6ncybNxZatWPHDp577jnKysqYP38+//3f/82sWbPw+XzS\nK2dkZIQJEybIcOWuri5JJ4Tg9/uxWq3813/9FykpKdTV1WE0GsnKymL+/Pm88cYbZGRk/F2fX8hD\nJRRUrVKpUCgUqNVq+vr6GB0dZcqUKXg8HpYsWUJPTw9nz56ls7OT9evXM336dF588UXeffddHn/8\ncf74xz++7xhut5v58+cTHR1Nfn4+JpOJXbt2YbVaOXXqFKtWrcLn85GSkoLdbmfu3LnA2O9WKCxk\nZGSEjo4ONm3aJAMtFAoFixYtYv369cycOZP6+nqam5tpbm7mF7/4hYzEE0Lg9XrlfBobG8MFPYx/\nGpejU/8/h9TUVEpKSjhy5Ahf/epXqaurk7fIo6OjtLS0YDAYUKvVjI6Ovs9SoLOzk9TUVMrLy4H/\n3VtdCEFvby8JCQlSHhkq4EqlUvK5er2ehIQEtmzZcskuVSEEWq2WU6dOyY5Fk8kkrWdhrIvTbrdz\n5MgRfD4fs2fP5uqrr6ayspKhoSGeffZZAB555JFLzrW1tZXTp09TXFwsPdM9Hg8vv/wy1dXV2O12\n1Go1er2evr4+BgcH5cZdaMTHx3P69GlJNQwMDEg6JHTBUqvVDA8P09/fT1tbG83NzZftD67VarFa\nrcDYHUl2djb79+9nxowZvPrqq+Tm5spN2MOHDzM0NIROpyM7O5svfvGLWK1WbrzxRn70ox+xdu1a\nvF4vXV1dpKSkMDw8LF9779692O126uvr6e3tJRAIEBERQXp6OiqVioceegi73S5dJH/5y1/idDox\nm810dXWRmpqKQqFg37590pbg7rvvBuC5555jwYIFGAwGdu/ezVe/+lVGR0e58847mTdvHq+88grd\n3d2sXbuW5ORkampqZNpWGGH8M/hMql/y8/Pxer2sXbuWo0eP8uijj/Lmm2/KDc3Ozk7sdjvNzc2o\nVCqZSxniie12uyzOF6sQzi9u5/9coVDQ29sdjvd0AAAgAElEQVT7gZukQgiGh4cl/x66oISCFEIY\nHh4mLy+PoaEhjEajlNL5/X6WLl3KuXPneP3111GpVDzyyCOcO3eOb37zm7z33nscOnR5/VtVVVWM\njIxIP5b+/n5UKhWnT5+WgdGhlvjQe1Cr1dJCwOPx0NbWJu0BQpx/SIFjNpsZGBhg+/btUmFiMBho\nb2//G7P6K0K6/7a2NkpLS9m9ezdLlixhz5499Pf3yzsIGLtTSkxMRKVSodVqef3119Hr9Wg0Gt59\n9126u7vZtWsXvb29NDc3c/bsWVQqFd3d3XR2dlJWVsa8efM4dOgQX/rSl2htbZUXooSEBFatWsX/\n/M//UFFRwQ9+8AO2bt3KlVdeSW1tLYsWLeLgwYM4HA6ioqI4duwYGo1GujBWVlai0+koLCzkscce\nIzY2lsbGRrZu3Yrf70epVBIVFUV9ff1lnZcwPt/4XKtfbrzxRrn52dbWxpYtW3A6nRdsQIXChY8e\nPSpTiz7oXPwtRUuoOI+Ojl6gST+fj7darQQCAbnaTk1N5fTp02RlZV0gh5w2bRoVFRUkJSXR0tJC\nT08PGRkZNDc3M336dBoaGj70hpTi4mKGhoaoq6sjLi6OoaEhRkZGpLFWREQEERERchUZDAb5+te/\nTm1trQzSbmxsxO/34/P5MBqNTJgwgV27dsljaLVaMjIyOHfuHM3NFzcY/224XC6uuOIKabIV8lnp\n7OzE6/UyPDyM2+3G6XQyPDzMjTfeyKpVq+jo6GDZsmXSglmlUjEwMIDVamXhwoUA3HDDDdx2220o\nlUpiY2NpamoiEAiQlJTEpEmTJN115MgRDAYDLS0tZGVlcfbsWXkhjo2NpbS0lJqaGo4dO0ZokbRl\nyxY2bdrEzJkzOXXqFC6Xi6qqKgYGBvja174mg9HDCONycbmc+mV5CXySg3/AI2HOnDlix44dYvbs\n2WLJkiXCZDKJ/Px8masZHx8vgAt8WUK+JQqF4gJL3kuNUCboxeNiy9SQlSogEhIShFqtlscIfa1W\nq0Vubq7Izc0VGo1GLFiwQD7nxhtvFD/72c/EuHHjpN/Jhz3WrVsn7XXj4uKESqUSHo9H+s3o9Xp5\nbtxut/TLueOOO+RrWCwWMX78eOH1esXChQsveZzk5OTL8tKBMatbr9crvF6vSExMFE6nUygUCpGT\nkyNfQ6lUismTJ4uMjAzx9a9/XURGRorFixeLvLw8odFohNPpFDqdTmaTejweERUVJcxms0hLSxNp\naWnC4XCItLQ0MXv2bBEfHy9eeeUVYbFYxHXXXSe8Xq8oLS0VNptNuFwukZCQIOLi4kRkZKRQq9XS\nCwcQ+fn5Ijc3V7hcLmEymYTJZBJ2u13Mnz9ffOlLXxLXX3+9uP3220VUVJT0CQIuyEgNj/D438Zl\n18xPumh/FEUdED/84Q9Fdna2SE9PF0lJSbKQulwuGegbHR0tjEbjBSZeoaJ1cQFSqVQXGGvpdDox\nderU9z324ueFgphh7GJwvhd56CIQ8g73eDziqquuEl6vV0RERIhFixYJvV4vFi5cKDwezwUh1f/s\nCJlH2Ww2MX/+fJGUlCSsVqtwu90y4DlUzEMB2ZGRkSI5OVkUFBSI66+/XhpjmUwmkZiYKLRarYiN\njb3k8ZKTk0VOTs5lzU2j0Yj7779f3H///QKQAd6hC1thYaF48803BSAcDodwOp1i1qxZQqlUitjY\nWJGSkiJ0Op1QKBQiKytLft5KpfICH/akpCSh0+lEYmKiuO6668RXvvIVMX/+fKHX64VWqxW5ubli\n2bJlwmq1ipkzZ4qMjAzpf2+z2YTH4xEajUY4HA5RWloqvvWtb4nCwkJRWFgojzFnzhwBiOLiYmnS\nZbFYLunfHx7h8bfG5dbMz6z6pba2ljNnzqBWq+nu7sZutxMfH8/AwICkYUJBwAqFApVKhdFolJp0\ntVqNw+GQrzcyMnKBMmFoaEj6k5xPzYQ00DCmojm/qclkMkkVSIi2mT59uvx5Q0OD1MbrdDpeeeUV\n5s+fz4YNG+Rm3oeF0F5AXFwc3d3dmEwmgsEgbW1t9PX1IYSQkXXXXHON1Lyr1Wqqq6t5+eWX0el0\n6HQ6NBoNtbW1pKamyiasi1FTU3PZnPrIyAibNm2SVgHnzp0jIyNDpkCVl5dz5513olar6ejoIC4u\njrfeeotly5ZJ7b3VasVisXD69Gmpp9doNJhMJjlCPjFCCLZt28a2bdt47bXXcLvdREREoFQq2bt3\nr4zG02q19PX1UVpaSkxMjAyoDjW0bdu2jRtuuIEbbriB9PR0ANncFB8fL6m57u7usA1AGB8ZPrNF\n/dChQ6xatYqjR4+i0WgYHR1lzpw5smADckNtdHSUYDBIX1+fNMCKjIykra1Ndk1erFTxeC7M+TCb\nzdK7JRRiEeKc7Xa7lK5t2LBBZpgWFhYSDAYlb52WloYQAr1eT2xsLPn5+bz00ksfyfkJacaFELS0\ntEj/FYVCQXR0NEIImpubSUlJ4ejRo7z22mtER0dTVVXFxIkTLzgXPp8Pq9VKb2/vBbF3F6Opqemy\n5hbir1taWsjLy8NqtWK1WklMTOTw4cPo9Xo6Ojqkmqajo4Of/exnbN68WcoaR0ZGGBwcxOPxSOWN\nyWSis7NT+tcfOHCAjo4Ourq6ZJHV6XS0trbK/ZimpiYaGxsJBoM0NDQwe/ZsqqqqpE9NUlKSNPFq\nbGzk2Wef5dlnn5Xn4dChQ/T29n5kn2MYYVyMz2xR37dvHz/60Y+wWCyMjo6Sl5fHgQMHuOKKK0hL\nS2POnDkMDg5SX18v03BUKhVqtVp2esKFXYchnB8qHbpAKBQKdDodCoUCt9sNIHMwOzo60Gg0dHZ2\nSq+ZSZMmUVtby/79+2ViUUxMDAaDAZVKhdPp5MCBAx/5eXK73Wi1Wtrb2+UFKXRxiYmJobq6mtjY\nWLnKnjlzJu+99x5CCKqrq6muriYvL4+ioiIaGxv/4XmEPFhgTBbpcrlwuVx0dHRw8803c+zYMamT\n1+l00qMnPz8fjUbD//t//4+kpCQGBgbwer3y/Zw5c4bh4WFsNhttbW3MmjVLBpTDmBwzLS2NyMhI\nurq6GBwcRAjBFVdcQXFxMcPDw/h8Ptmc5Pf7CQaD7Ny5k7i4OOm6GDIzKysro6ys7IJN+cTExH/4\nvIQRxt+NT5oz/6g49dAIBS5otVphsViEwWCQG5hOp1MkJCRcEMoQ4s1DuZihMIrQOH8zNMSRWq1W\noVQqxZIlSy7g1EO8aUJCgjCZTEKhUAiz2SxSU1NlEMXkyZPFtGnTxLRp0+Rm3Je//OWPjafLzc0V\nRUVFwuVyCZ1OJywWiygtLRUOh0MAYtKkSSI2NlYkJCQIvV4v8vPzxYwZMwSM7RdkZmaK0tJSkZiY\n+E/Nw2QyyU1inU4nvvWtb4lvfetbwuPxXLApC2PBJOfz5GazWUyePFloNBqRm5srz7lKpRLp6elC\nrVaLZcuWiYiICGE2m4Xdbhd2u11uiKtUKqHRaGTghV6vF1FRUSIjI0OkpaUJq9UqCgoKxMqVK0Vk\nZKS46qqrBCDfs0KhEA6HQ8TGxl6wPxMe4fFhjs89px5CfX09mZmZrF27lu7uboaHh0lPTyc9PZ3u\n7m5aW1s5fPiwpBNsNhsKhYLp06eTlZUlaZYQfxwMBvF6vcTGxkrawufz8b3vfY/GxkasVisqlQqH\nwyFX/g0NDSQnJ+NwOOjp6SEuLk7K68xmM9dccw3XXHMNMTExZGZmygaijwM+n4+zZ89yzz33MDo6\nitFopKamRt6J2O12YmJi6OzsxOVySc/x5cuXYzAYMBgMdHV1XTa18kFITExk06ZN3HLLLQwNDXHo\n0CEOHTpEZ2cn+/fvJzk5mbS0NACEEHLFPmvWLHp6eqiqqiIQCHDw4EFiY2Px+XzSpmDBggW88cYb\nGAwG2fLf0dFBMBgkLi5O3pWFVumhXobW1laqqqpITk4mKyuLbdu28d3vfpeCggJ27dqF3+/H6/WS\nlpaGwWCQtgrn77GEEcbHjk96Jf5Rr9RD4/rrrxcajUYYjUa5aoYxZcf5CpW4uDihVquF0+mUK/h5\n8+bJnysUCmGz2YTNZpOvYbFYhNvtluoWrVYrX/N82eTEiROF2WwWKSkpwuFwiMjISLF8+XLh8XiE\nx+MRX//614VOp/vYVwALFy4UWVlZIi4uTpjNZjFx4kRhMpmESqUSarVaTJ06VWRlZYnY2Fh5B2Oz\n2cSNN94obrzxRrFly5YPZR5r164VM2fOFFdeeaWYNWuWmDVrlnj88ceFQqEQTqdTSklDUkClUnlB\nJODEiRPlYw0Gg1i6dKkYN26c0Ol0YuHCheKb3/ymyMrKEmvWrBFr1qwRKpVKqlPUarVcucfExIjF\nixcLGItEtFgs8m7GbDaLZcuWCeBDVSOFR3j8b+Oya+YnXbQ/rqKuUCgklZKZmSmio6OlxE6lUol5\n8+YJq9UqJk6cKAwGg0hKShKALBopKSkiJSVF5OfnC4fDcYGOG8ZoHrPZLFwul1Cr1cJoNMoiMWHC\nBOFyuURkZKRwOp3iX//1X4VGoxEPPvigKCkpEQ899JB46KGHPrFfltTUVBEXFyemTJkiEhMTRUJC\nggDE3LlzxdSpU4XVahUxMTHil7/8pXxObGysKC0tFaWlpWL69Oli2rRpUkZ4qWPcddddl8zdzMvL\nEwqFQtx3331ixYoVIjc3VxgMBpGVlSWysrJEYmKiyM/PFzExMcLj8Ui5Z0h2GXqdUFZrUVGRzFAt\nLCwUHo9HxMXFCbfbLZRKpbj11luFwWAQBoNBOBwO4XA4ZN/CCy+8IDIyMsTPfvYzUVBQ8D4pJYxR\nQzNnzhRPPPGEuOmmmz7xP/Tw+PyMy62Zn8mO0r8Fj8eDx+Ph1KlTtLe3o9FoCAaDWK1WoqKisFqt\nVFRU8MUvfpGKigqOHz/OpEmTpJqho6ODvLw8GhoaOHfuHL29vdLfxev1UldXRzAYJD8/nwMHDpCU\nlCQ9VHQ6HUIIvvrVr2KxWFi3bh233347X/va1z7Mt/h34/777+eNN96gv7+f3Nxc3n77bfR6PRMn\nTuTAgQNSBTM4OEh7ezsOhwObzSZpi9jYWPr7+6mtraWhoeGSx3C5XAwMDEifnenTp3P06FESEhKY\nOHEiTz31FAUFBfT39xMbG4vdbgdg69atREdHSyuH1tZW9Hr9+7zZ1Wo1c+fOZdOmTTI1KtS5azQa\nMZvN6PV6zpw5I62O29raaGhoYPXq1axZs4aioiIee+wxqarRaDQUFBQghODw4cOUlpaiVCo5ePDg\n390ZG0YY/yzE592l8YNQX19/Qat9yORr/PjxnDlzhqGhIUZHR9m9ezeFhYXSy6O1tZXW1lZ0Op10\n57Pb7URGRpKbm4taraa/v59gMEhBQQG1tbXSnrarqwuVSoXf72fOnDky//ORRx7h9ttv/wTPxhgU\nCoXUdR86dEja0e7bt4/m5mZsNhv/8R//wYwZMxgaGiIjIwOr1Sr3Jurr6zGbzZcs6EajkeLiYubP\nny8L+qxZs0hMTKStrY3k5GT27NlDXFwcer2e7u5ugsEgu3fvZvfu3RQXF8tkpKamJkZHR99X0JVK\nJdnZ2ezatYv09HS0Wi0ej0emLsGYnLKtrQ2r1UpMTAwxMTHExsai0+n4j//4DyIjI5k/fz6/+c1v\nmDt3LgaDgZiYGOkJlJmZyRtvvMHrr78eLuhhfKrxuSvqIbS3t6PX65k+fTo6nY5HH30Ur9fLkSNH\niI2N5Zvf/CZPP/00w8PDpKSkSG1zMBiko6OD9vZ2jEYjWq2WQ4cOERkZiVKpJD4+nurqanp6etDp\ndERHR8tGlqysLHbv3s3NN9/MwoULmTVr1qfCavXQoUMyRi8uLo6SkhJaW1sZGhpCq9XidDrZsGED\na9euJT09nfb2dg4ePIjP58Pn8+F2u9m8efMlX/vaa6/FYrHIgh8ZGUljYyN79uzh1ltvpbOzk7Nn\nz5KRkYFSqaS5uZlFixZhs9mw2Wy0trYihJDRdZcK/hgdHaWhoYHbbruNpUuXyqi92NhYrrrqKmBs\nA9zlchEbG0t9fT319fU0NTXx85//nP7+fnw+H3V1ddLWt6CgALfbTTAYxGAw4Pf7yc3N/Yg+gTDC\n+PDwuS3q8Ncc0PHjx7Ns2TJqamr40pe+RH9/P/fcc48MGj569Ch+vx+/38+kSZOAsbi8hoYGSR+E\nsikBhBhzL5w6dSrd3d24XC4MBgPJyck88sgjbN68+QM7Lz8JhAKcTSYTQ0NDtLS0cOrUqTF5lFKJ\nXq/nqaeeIjs7G4PBgM1m49prr0Wv16PX6z9Qnz558mSsVisNDQ1kZWUB8J3vfAeHw8E3vvENampq\n2LZtG729vSxatIjBwUGuu+46/vznP8vmo+rqannHFEowuhTa2tpQq9VUVFSwYsUKmpubMRqNaDQa\nfvWrX2E0Gqmurub48eMMDAxIu+Cnn36auLg4ent72bp1K2vWrOHMmTOoVCrZZbtr1y5aWlrQaDQU\nFRXJ4Oowwvg04nNd1MMII4wwPmv4TIZk/D1455135Ncmk4n169ej1+tlcMHs2bN55513pA9Mf38/\nDoeDpqYmcnJy5Er+lltu4be//S2LFy/m4MGDDA0N0dPTg1KppL6+HrfbjUaj4b777vvUcbL//u//\nzrp16/D5fLS0tDBz5ky++tWv0tXVRVRUFG1tbbjdblpaWqQnuE6nk+cu1GIfGxtLc3MzDoeDtLQ0\nTp48SVxcnLRBmD59OhUVFdTU1NDc3Mzw8DAej4dly5bx6quvsmjRIk6ePElbW5u0WkhLS+Pdd9/l\ne9/7HjU1NTzzzDOXfA8RERFUVlbS0dFBfX09M2fOpLe3l2AwyMaNG1Gr1Vx77bV0dHRIHXlcXBwa\njYbExEQOHDggveF37NjBpEmTUCgUREZGEh0dTXd3N9XV1ajV6veFqoQRxqcJnzv1y6WgVCrRaDS4\nXC7OnTvH6OgoHo+HkZERqqurUSqVFBYWArB//36USiUulwuTyURXVxculwutVotGo8Hr9fL000+z\nYsUKNm3ahMViwePx4HA42Ldv3weqQz4pJCcnS6+VO++8kzNnzrBmzRoyMjKYPXs2jz76KAC33347\ndXV1VFdX4/V62bx58wVNNuPGjWNgYEBmb3Z0dJCVlcXWrVtJSUkhOzubY8eOYbPZ5IZoeXk51113\nHadOneLAgQPcddddlJeXYzQapXnZvHnzOHHiBC+88AI333wzTz311AXzz8zMJCMjg87OTjweDy0t\nLZw7d46srCyOHDlCUlISEyZMoLOzk9///vf84he/kBeMNWvWoNFoaG1tZfz48axfv56srCx54dbp\ndJKmCTVXhewcQmHcYYTxcSGsfrlMaLVabr/9dlJTUzl79iwRERHExsbicrl4/PHHSUpKQghBW1sb\nbW1t6PV6nE4nU6dO5ciRI7KY7969m8cee4y9e/dy8803s2bNGoxGIykpKVRVVfHKK6986go6jLkn\nhvjqsrIyenp6uOWWW9BoNPT19XHfffchhGD9+vWSz963bx+jo6OsWrWKVatW4XA4MBgM9Pf3yzsS\np9PJoUOHmDFjBm63m46ODnQ6HVqtlujoaLmP4ff7sVgseL1efvOb32A0GmWA89GjR0lJSeHNN98k\nNTWVF1544YK5W61WkpKSeO+99xgeHmbr1q0sXLiQ3t5euQHt8Xh48cUXufrqqxFC8Nprr7F27VrW\nrl1LfHw8UVFRGI1GNm/ezL333isdHW02G4cPH8bv92M0GhkaGsJms2E2m8MFPYxPNT73RT2USv/N\nb36Txx57jBtuuIHi4mKsVisrV66U1qohl0an00kwGOTEiRMYjUaUSiUVFRU8+eST3Hnnnbzxxht4\nvV6USiVz5szB5/N96ovAgQMH0Ov1JCUlsXv3biorK1mxYgUvvPACZrOZ2267TSp48vLyKC0tJT4+\nnrfeeou33nqLtrY27HY7CQkJXHXVVWi1WuLj40lMTJQpQT6fj4GBAVQqFdu2beP06dP8+c9/pqOj\ng3feeQelUsmNN97I0NAQTqeTnJwccnJy2LRpEzabTcbsnY9FixaxY8cOmpubcTqdZGVl8etf/5rU\n1FQmT55MYWEhtbW1WCwWqqqqUKlUWK1WOjs76ezspK+vj61btwKQm5vLc889R1RUFN3d3Zw8eRK7\n3U5raytNTU14PB70ej0TJkz4JD6iMMK4bHwmM0r/XlRUVLBhwwZee+01ysvLUSgUtLW1ERMTQ11d\nnfxjjo6OZmRkREa3ZWZmyhi82tpaXn75ZZxOJ/fddx+9vb0cOXLksnNDP2mEvF1CEs+uri46OztR\nq9WcPHmS9PR0Tp8+LYvili1beOuttzAajVLaGQgE2LFjBxaLhVOnThEVFUVTUxNRUVGUlJRQVVWF\nXq9n//79jBs3jhMnTlBSUoLD4SA9PZ133nlHatBDcYFVVVXMmTOHEydOvM/Wd3R0FL/fT35+PvHx\n8fj9fhYvXkxHRwdHjx7l+PHjsq+gp6eHpKQksrKyWL9+PW1tbcycORO1Wo3BYODgwYMMDAxIBVPo\nDiw+Pp5gMEhXVxejo6M4HA6ZXxtGGB8nPtcZpf8sIiIi0Gq1lJSUUF9fj8fjkX/sc+fO5Z133kGt\nVlNXV0d6ejqzZ8/m8ccfR6PR4PP5OHny5P85Uye9Xs/SpUs5ceKE7KJsaGggPj6ejo4O3nzzTSZO\nnMjOnTv56U9/Sl1d3QWe4ZWVlUyYMIHMzEy2b99OXl4ekyZNYu/evbjdbtasWcP8+fN5++23pXd7\n6CJ5880389xzz9He3k5WVhZCCJmJ+uabb3Ldddexfv36C+ZbUFDA6OgoAF1dXRgMBvr6+nC73Rw+\nfJi8vDxMJhPV1dWkpqbKjtempiacTicAPT09ZGdnc+TIEYQQaLVaurq6GB4exuVycf311/O73/0O\no9FIVlYWhw8fBpCa/tDxwwjj48Dlcurhov4BCCUQhf5wIyMjgTE3wS9/+cv89re/xWw2X5Bs9H8Z\narWau+++mz179mC321EqlajVanw+HyUlJTz88MMkJCQwZ84cDAYDu3btIicnB4BnnnmG8ePHy83F\niooKvvzlL7N582bi4+NlwXz77bfp7e3FZrORmZlJXl4ehw4dYnBwkOzsbP785z/T399PcnIyUVFR\nABw+fJgJEyZQUVFxwXxvu+02ysrKaGhooLe3l0AgwNSpUyksLGT16tWkpKRQX1+PxWIhMTERnU7H\ne++9x5IlS9i4cSMwtkGu1Wppa2uTtg6ZmZl0dHRI9VJWVhaNjY0y8HpoaEjaCIQRxseJcFH/CGEy\nmT7UaLlPA6666irOnj1LWloadrud9vZ2li5dyu9//3u56Tl//nz27t2L1+vF7XazevVqABwOBxMn\nTqS6uprbb7+d9957j2PHjhEfH4/H4+H48eN0dnbS1dVFREQEycnJbN++nZ///Ods3ryZiIgI3n33\nXZYsWcLQ0BDt7e2StpowYQJvv/32++ZbUFBAQ0MD3d3dxMTE0NTUxPLly3n++ecpKCigoqKCmJgY\njEYjXV1d5Ofn09nZicFgoKamBkDSQ2+99RYLFixAoVDQ2NhIZmYmMTExHDx4EK/XS0ZGBq+88go5\nOTkEAoH3XWDCCOPjQFj98hHis1bQNRoNb775JlOmTMFsNrN161ZSU1P593//d5YsWYJGo6GxsZE5\nc+ZQWVnJwYMHJXdusViYNGkSDoeDhIQEXnzxRQC8Xi8dHR1UVVVRWVnJsWPHUCqVrFq1ivr6eubP\nn49KpWL//v3U1tbKwjlu3DiUSiWDg4MMDg5SVVUlFSkhKJVKuru7pTIptBrfsmWL9KIJtfj39/ej\nUqkoKyujt7cXnU6HWq2WPvdDQ0MUFBQwMjKC0WgExui3EydOSO+X8vJyvF4vvb294YIext9ESC57\nfiJa6N9QlOb5UZAfBcIr9TAkrrrqKt58800KCwtJSkrC5XJRV1fHuHHj2LJlC3l5edjtdioqKigr\nK5PF9tprr+WNN95Aq9XK0GchBBEREYyMjODxeFAqldTV1WGxWDh58iRGo5GoqChyc3PlBmpFRQVR\nUVG0t7eTkJAAjDV7XbwxmZCQQGdnJxMmTKC8vBybzSapshDP7/V6GRkZoa2tDYfDQW1tLXq9nhUr\nVkh+3ufzIYTA4/Gg0+nk5q7RaJTHjIiIQAiBzWZjcHCQQCAg+f4wPr9Qq9UyX/hSkZcfBcIr9TD+\nbpSXl3PbbbexfPlyFi9ezIEDB0hMTGTfvn0cPHiQo0ePEhUVRU5ODgUFBXI1XVtby/Tp07Hb7dKI\nS6FQkJSUxIIFC0hKSqKsrIzo6GgaGxuJioriqquuwmAwXJAlGggESElJIT09nebmZpqbm9FqtXJ+\noYuIVqslIiKCAwcOEBERQTAYxGQykZubKzNe/X4/tbW1OBwOGhoasNvtmEwmXnzxRSIjI4mMjJRh\n4O3t7dTU1ODxeOjs7CQmJgaz2YzD4UAIQUpKCv39/fT19YULehgABINB4NIZxp80wkU9DImenh4K\nCgrYs2cPv//97/F6vZw8eZKysjKcTicul4uGhgap3S4pKaGkpASdTsfrr7/OrFmzyM7OZsmSJWRk\nZPDuu++yZcsWnnvuOfLy8qiursbtdhMIBHj55ZfJy8tjy5YtJCYmIoTA6XSyZ88eKioqpANkKJD6\n2muvZWBggPnz51NVVYXVasXpdCKEYNy4cUyfPp3S0lIUCgUGg4HGxkbMZjNdXV2MjIxIW+RgMCiN\nyE6fPi07YUP7CPHx8ezbtw+73U5aWhpxcXFSY/9JIqSxt1qtlJSUYLVaP9H5hPHpRZh+CeMC7Nix\ng0WLFqHValmxYgU+n4/t27ejVquls+If/vAHhoeHZdfm6OgoS5YsoaurS+rarVYrNpuN4eFhvF4v\nzz33HOPHjyc2NlY2Y9ntdvbs2UN/fzi1pu0AACAASURBVD/Tpk3j1KlT9Pb2Mjg4KC1zt2zZcsH8\nCgoK0Gg06HQ6Sa1ERUWhUCjYtWsXra2tREdHMzo6SmdnJ1FRUQwPD9PX10dVVRWFhYXSu8XlctHc\n3IzdbufcuXNS3bJ69Wr+5V/+BbfbLf1jAoEAEydOpKys7GP8NP6q17fZbOTl5QGwbdu2j3UOYXw6\nEKZfwviHMHXqVBQKBXl5eeh0OhQKBZMnT+bZZ5+lpaWF7u5uiouLue+++8jLy5Or7dzcXI4fP87B\ngwe54oor6OjoYHBwELvdzjPPPMOVV16JwWCgsrISi8WC1Wpl3759uFwuHA4H27dvx2q1EhcXx+TJ\nk+nu7qa7u/uCud1///1otVoGBgbYvXs33d3dGI1Gjh8/TmNjI0ajka985Suo1Wrpv26z2WRAdlFR\nEQqFQq7Yz507R3x8PIFAAK1Wy9DQEF6vl5/+9KdER0eTlJREb28ver2eYDD4sdklazQakpKSMBgM\nciO4q6vrkuckjDAuRrioh3EBXC4XgUCArKwsdu3aRWxsLH/605946KGH2L9/P9XV1VRUVHDgwAGZ\n6vT000+zbt06hoaGKC4uZs+ePZjNZlpaWtDpdMyePZuamhpOnTrFlClT2LFjB+PHj8fn8zE6OsrI\nyAgKhYLf/OY3mM1mqqqqePjhh3n44YflvJYsWcK5c+c4c+YMVVVVzJ49G5PJxK5du4iPj6etrY2h\noSH+53/+B7fbzcSJE1EoFLIo9/f3093djUajISUlhZSUFFasWIHf78dgMBAREUFJSQkRERH4fD5W\nr17N/v375Ybvd77znY9N9RQVFYXH42FgYICIiAi6u7v51a9+RUVFRVh9E8b/ijD9Esb7EBkZyZ13\n3onFYqG7u5tXXnkFi8XC8ePHSUpK4qGHHuLee++VfHdBQYFs1jl+/DjBYBCbzUZvby+JiYmUl5fj\ndrtJTU3lnXfe4a677uKxxx5j8eLFvP7666hUKlwuF/39/eh0OjIyMsjOzgbgkUceAWDatGkcPXoU\nrVbLyMgINpuNmpoaKWEcHR1Fp9OhUqlob2/HarViNBo5c+YMWq2W4eFhtFotg4ODxMfHA2Odoefb\nEmRlZREIBIiMjOTIkSOo1Wp0Oh0+nw+73c7g4OBHyq3n5uYyMDBAZ2cnHR0dpKen09PTg8lk4tSp\nUx/ZccP4v4Ew/RLGP4SQ2+IjjzzCoUOH6Ozs5MEHH6S8vJx58+axdOlSHnjgAerq6pgzZw5z5syh\nqqoKn89He3s7U6ZMQa/Xk5OTQ2xsLCtWrODKK68kKyuLtLQ08vLy2LFjBx6Ph+3btxMVFUVMTAzD\nw8O0tbXhdDo5d+6cVL/AmHyspaWF5ORkdDodEyZMoLu7G6fTyQMPPIDH45Ebq2q1Gr/fz7Rp0+Tz\n/X4/DoeDQCCAxWJBq9XKTlL4K2/d2dmJzWbj+PHjREZGUlpaKiWSQ0ND8iL2USAuLk5G7YW6br1e\nL+PGjfvAZKkwwrgUwkU9jAswMDDArbfeilKp5NZbbyU1NVUWttCqvbKykilTpvDEE0/wxBNPMGnS\nJJqbmwkGg7z11ltce+217Nu3j+nTp/Pkk0/icrmoqalh3bp1tLe389vf/haFQoHFYqGtrQ2TyYRK\npSI9PZ2ysjIqKyuZPHkykydPJisriz/+8Y8ybCMUQA1jevUnnngCn8+Hx+Nh/PjxBAIBrrnmGtav\nXy8bQHQ6HT09PYyMjFBSUsKZM2c4c+YMhYWFxMTEXNBAZTabGRkZkaEb6enpvPTSS/T3939glN6H\ngfj4eDo7O8nOziYQCFBYWEhzc7PcSA4jjMtFmH4J43340Y9+xL/+67+i1+s5c+YM+/fvx2w2S5XL\n5MmTOXz4MNOnTwegoaEBl8vFkSNHGB0d5c477yQtLY2cnBxuu+02xo0bh1arZdOmTXR1dTFr1ixe\nf/11hoeHMZvNBAIB6ave399PT08PP/rRj4Axjv/JJ5+ksrKSwsJC6uvr0Wq1jI6Oolar6ejoQKFQ\nkJ2dzfHjxxkdHZUUSm1tLcnJydTX1xMMBlGpVFLVA3Dy5El2796N2+2mp6eHjIwMysvLMZlM9Pf3\nYzAYiIqKori4mFOnTlFZWfmRnO+oqCiuvPJKdu3ahUqlorS0lJdffplJkybJ/NgwwgjTL2H8w/je\n976HXq8Hxjo6MzIy+PGPf8yf/vQnNm7ciMlkIi8vj/T0dNLT02lpacHhcJCYmMh1113HU089xapV\nq3jppZf4+te/TkNDA0ePHuXqq6/GbDazbds2mYbU0dFBV1cXycnJMjnJbDYTHR1NdHQ0bW1tHD9+\nnNdee42DBw+yYsUKlEolTU1N+Hw+8vPzpXVuVlYWwWCQjo4OIiIiiI+Pp6amBrVajd1ux2w2o9Vq\neeGFF3jhhReoqalhwoQJTJs2jUAgIJ01Fy9ejNPpJD4+Hp/Px6uvvkpSUtIFjVAfJqZMmSK7bXU6\nHeXl5WRlZXHgwIGP5HhhfMYhhPhUD0CEx8c/Vq5cKdLT04XP5xO33HKLmDZtmnj66adFQkKCAMTX\nvvY1kZ6eLtLT08XPf/5zkZSUJIqKiuTzly1bJiZNmiSWL18uFAqFWLhwoYiIiBDFxcXirrvuEoBw\nu93CaDQKi8UiYmJixLhx44RerxexsbHihhtuEDfccIMoLi4WmZmZIiEhQeTl5Yn4+HjhdDpFdHS0\n+OEPfyhsNpsoKSkRd9xxh7j66qtFXFycUKvVAhBOp1Pk5OQIjUYjEhMTRXR0tNBqtXKOQgiRmJgo\nAJGRkSGioqKE0WgUdrtdaLVa4XA4hE6nEzNnzvzIzvOKFSuESqUSGo1GZGZmiujoaHHttdcKrVYr\nHn744U/89yA8Pj3jcmtmmH4J45Kw2Wz09PRQVFREZ2cnx48fZ8WKFbS2tuJ0OmWOJ8Bzzz1HWloa\nAwMDtLa2cscdd1BWVoYQgr6+PrxeL0ePHkWj0WCz2Th9+jSLFy/m5ZdfRqfT4ff7aW1txW63k5mZ\nSVNTExqNBhjzSh8aGsLhcNDY2EggECA9PZ3BwUG+8Y1v8F//9V9oNBpOnDjBNddcw8GDBwkEAni9\nXhmcffLkSTIzM/H5fGi1WumLPjAwgNfrxWw2c+TIEcaPH09jYyMlJSVs3LhRBmmnpKTQ0tLyoXPb\nhYWFREREUFVVhU6nw+Vy4Xa72blzJzk5ORw5cuRTn5oVxseHMP0SRhhhhPE5RLioh3FJhDxTsrKy\n+MpXvkJsbKwMlj569Cg7d+5Ep9Oh0+lYtWoVHo8Hk8nE7NmzWbt2LeXl5bS0tEijLrPZTDAY5PTp\n07hcLjZu3Eh6ejoKhQK/349CoSA6Oprdu3dz6tQpaVU6MjJCMBgkPj4ejUYj7QhGRkZ44IEH0Ol0\nJCYmkpGRwWuvvUZ3dzd+v5/6+nra2trYsWMHo6OjVFZWUllZydmzZ9FoNGg0Gr797W8zODiI0Whk\n8uTJHDx4kEmTJvHWW29JU7DCwkKGhobeZ//7YaCqqorx48ejUCjIz8+nurqa5uZmAoEAO3fuDK/S\nw/iHEKZfwvibmDp1KsPDw9x11108//zzdHR00N/fj81mk46FGRkZbN68mcmTJ5OYmMgrr7yC2+2m\nvr6e4eFhTCYT9fX1xMXF8e1vf5sHHniAcePGcfjwYYQQaDQarFYrra2tBAIBVCoVycnJwJivzODg\nIE1NTSQnJ9Pb20t7ezsqlYp58+Zx+vRpSctce+21tLa2smPHDjIyMjhx4gQWi4VAIEBMTAwDAwNE\nRkZSVFQEjGXThuwEQsW9urqa6dOnc/DgQcxmM7W1teTm5nL48OEPPe3oC1/4AqdOnaKzs5P29nau\nu+46Tp48iUqloqenh5qaGhmdF0YYYfoljA8Fg4OD/OpXv8JsNqNWq2XKkNlsxu/34/f76erqYvLk\nyXz3u99lx44ddHR00NPTg9vtpq+vj5/85CdkZGTQ1dXFnj176Ovro66uTtrzhsIuAIQQmM1m2djk\n9/tJTEzEZrNx9uxZVCoVqampaDQaZs6cic1mk1z00NAQMBY52NXVRXR0NAkJCVLe2NfXR0tLi1S/\n/PjHP5ZReCETsClTprBz5056e3upra3FarVy8OBBqXn/sGCxWKiqqiIyMpLCwkImTZqERqMhKyuL\n1tZWvF4vc+fOxeVyfajHDeOzj3BRD+NvIuRM+OMf/5j8/Hzeeecd3G431dXVjIyMyBAMl8vFF77w\nBWJiYnA6nfh8Pvbu/f/t3XtY1Ned+PH3mRtzYxgY7iADcheLCsZ4TTVajdaqu0nTpNlfG6vpdp9f\nk93tr2mfX3d7iX3STZ52292NTdunzUYTm7a5mHSTqrHeYrzEGyqggMj9OjAoMAMMDMP398fA96cU\nI1GUS8/reXhwvvOd4Zzvwc8czveczzmF2Wzmu9/9rrrkfc+ePcyePRu9Xs/jjz+Ox+Ohvr6evr4+\n4uLigOB2gVu3bmXr1q1oNBqKi4tZv349iqJgNpsxGAzMnj2bX/7ylxQVFWE0GnE4HFRUVHDkyBES\nEhLo6upSN/lIT0/H6XTS09NDIBBAq9Wi1Wp56qmn6Ovr48qVK3R1ddHY2MiZM2dISkoiJSUFh8NB\nREQERqNRzZA4Vjo6Opg1axbz58+ns7OTDz74gMOHD2MwGNDr9fT29nLy5EmWLl1KWFjYmP5saWqT\nwy/Sx9JoNPh8PgwGAw888ICaAXEoEEJwByGTyUR8fDxer5ekpCROnDjBpk2beO211xBCYDQamTt3\nLq+//jqxsbF0dnbS19enztGOjIykuLiYefPmUVVVxbJly4DgwqYPPviAvLw86urq6O7uxuv1kpKS\nQn9/P8nJyXR0dKi5Wnp6enjyySc5cuQItbW1KIpCZ2enmne9tLRUnbUTEhKC2+1mYGAAm80GQEJC\nAqWlpZhMJrRaLWFhYWi1WsrLy8f82mZkZDB79mx27dpFamoq58+fV59LT09Hr9dz8eLFMf+50uQk\nN56WxtTmzZtJSkri3XffZfr06bz77rv8+Mc/BuDEiRPs2LGDhQsXcuXKleuyMS5atIijR49iMBhI\nSkpSdzqy2WyYzWY0Gg2ZmZkcOnQIi8WC1WpFr9fT3NwMBFdbVlVVkZqaqk577O/vZ9asWbhcLpqa\nmpg1axYRERG8/vrrrF27lg8//JDQ0FB1y7He3l5MJhNVVVXY7XaWL18OBD+w/vCHPxAeHq4mAps9\nezaFhYVYrVb8fj8LFixgYGCAQ4cOjXhdNBrNLY+1a7VaEhISqK2txWAwsHbtWvbs2cOCBQvQarXs\n3bv3lt5XmppkUJfG3A9/+EO2bdtGfn4+r7/+upomQKPR0NbWRn9/P/X19TidTtxuN+3t7djtdjWN\nbGtrq5p1cNq0aZw+fZrk5GS++c1vsm3bNtrb22loaMDpdBIZGQlAY2MjfX191NfXYzKZePjhh9m/\nf7+6V+jQ+LnX60UIgV6vx+fzERsbq25GDcEPh9jY2Ot6vvn5+Zw5c4aYmBhcLhcLFy6ksLCQ2NhY\nFEWht7cXt9utjtUPl5iYqGZVvBXTp0/HbDaredwDgQBXr14lKirqLzYHkSR5o1QaU1qtloaGBqKi\nokhKSmLJkiUcP36c48ePo9PpqK6uxu12Yzab6ejoUHvVLpeLkpISysvLMZvNxMXFERsbyze+8Q02\nbtzInDlz+NnPfkZtbS2PPPIIPT09lJaWql9erxe32016ejoxMTH86U9/wmQyceXKFdLS0mhtbVWz\nLl69epWsrCyio6Nxu938+c9/JiMjg4SEBBwOB3FxcWpKXwjuvBQbG6uOsR87dgyv10t8fDzd3d0I\nIcjOzh7xepjNZurr628ryVdYWJi6yXZtbS2HDh26blcmSboVsqcujcq0adPIy8vDaDTS39/PsWPH\nyMzMBODcuXPqUMX+/ftZunQpra2t9Pf3Y7PZqKqqorOzk5kzZ9LY2EhISAjV1dUYjUbi4+NJS0vD\nZrPx5ptv4nQ6iYqKUvOexMTEEBoaSmNjo7phxLx586isrMTn8xEeHq7mSC8sLFR3KRrad/See+5h\nz549WCyWEVeEZmZm0tjYyNq1a9XsjREREaSlpbFjxw6ioqJuOLyydu1a3nvvvVu+pkIIFi1axJEj\nR9i8ebO6AYjL5ZqQGxpL40sOv0hjLjk5mVmzZuHxeDAajWrSr9LSUnVmyVBA1mg0aDQaDAYD/f39\n6HQ61q1bR2VlpbowKC8vj46ODgKBAG1tbRiNRjIzMykqKmLOnDkAfPDBBwQCAfx+P+np6erWdMeP\nH8dut6PT6dBoNOj1ekJCQtBoNLhcLjwej7qLE4DNZkMIQVVVFTk5OQCYTCaam5vp7e1l8eLFvPvu\nu0Bwp/j09HQaGhrw+XwjBvX09HQyMzNvK6jbbDbi4+OJiYnh0qVLmM1mKioqbvn9pKlNDr9IY666\nupq4uDhWrVpFe3u7uuqzurqarq4udbeh9PR0AFJSUggPD0dRFPx+P0VFRYSGhrJ8+XJMJhP/8A//\nQEhICF/96ldZv349V69epaioCJfLxb59+9i3b5+6V2hWVhbV1dXqjJWYmBji4uLo7+/H7XbT0tKi\nrli1WCwkJCRgt9vxeDw4HA58Ph9tbW2kpaVx4cIFLly4gMvlor6+nvXr1/Pee+/R39+vzpdPSEjg\na1/72g176Tk5Obe9X+jQDKDS0lJiYmKorKy8rfeTJJBBXfqEPv/5z3PgwAEyMzPVjZCTk5NxOBzY\n7XbOnDlDdXU1f//3f09zczMejwefz8eaNWtobW2lo6OD7du3k5qaype+9CW6urrYu3cve/fuxW63\nEwgEuO+++1iyZAlLliyhvr6eadOm0draysDAgDrm3NXVRUlJCe3t7YSGhmK1WqmtrSU5OZmUlBQ6\nOjoYGBggISGB8vJympubCQsLw+/343A4cDgc1NXVYbFY+M1vfkNWVhZarRYIrvQ8dOgQpaWlN7wO\nLpdrTHKd+3w+ZsyYQVVVFRP9r2ZpcpDDL9InEhcXx9KlS6mrq1O3iwsJCcHn82EymXC73QQCAex2\nO21tbfj9flasWMGxY8dQFIWwsDB6enrUYDx79myKiopwOBwUFhaybt06ampqKCkpAYJ7k1ZUVKib\nZ0RGRuL1esnJyeHSpUskJCRgMpk4efIkWVlZGI1Guru7qa2tpaurC0VRsFgs6l8ViqKoM2vcbjde\nrxebzUZoaChLly5l3759uFwudYMMt9tNYmIily9fVq+B0+kkNjaWEydOjMk1jYqKUrfWk6QbkcMv\n0h3R1NSE3+9n1apV142bL1q0iKSkJDUvjKIoREdHq8m7NBoNHo8Hq9XK1atXiY6OpqWlhZKSEnVu\ne15eHseOHaO9vV2dsuj3+9Hr9RgMBgYGBhgYGMDv9zMwMEBUVBQ9PT0cO3YMq9WK2WxWe/Rer1ft\n+TocDrxeLx6Ph+7ubnp6eujp6cHr9QLBYaKGhgbeeecdbDYb4eHhJCUlsWHDBiIjI+nv77/uGiQl\nJV23UOh26HQ68vPzx+S9JAlkUJduwZtvvqnOOBnKnvjRRx+pN0iHVml6PB6cTicajYbdu3cTHx9P\nQ0MDdrudpqYmddl/WFgY4eHhFBQU4Ha76ejoUDMpnj9/npkzZ+LxeJg+fToGg4F/+Zd/UYPzjBkz\nePTRR4mJiaGjowOv10t7eztLlixBr9fjcDiora1lxowZxMXFMTAwgMvlwuVyqUnDioqKsFqtas8+\nMzMTo9HIwYMH+exnP0t1dbVad51Oh8lkuuHc9U8qOzubgoKCO7arkvTXZ2yzFEl/FfR6PZcuXcLt\ndgPBIZmQkBB1JWh6ejo1NTWEhYWRmZlJVVUVn/vc57Db7bS0tHD16lVWrVrFrl27KC0tZf78+eh0\nOjo7O1m4cCElJSVq0BzKLxMXF0dZWRkxMTF8+OGHCCFobW1l586dagrfoQ8Dn8/HpUuXmDFjBi0t\nLepy+6ysLB544AF12OTSpUuEh4fT3t6u9sY9Hg+XL1/m5ZdfJjw8nA0bNlxX97S0NOrr68fkOgoh\nKCsrIz4+XqbZlcaMHFOXPjEhBA888AAvvvgiENzTMzk5me7ubg4cOHDdcMWCBQs4fvw4EBw7NhqN\nXL16lWnTpqnj5tOmTcPlcrFgwQI1m6LT6QTg4sWLGI1GdDodFouF5ORkrly5Qk9PDwaDge7ubuLi\n4rh48SJ9fX10d3czZ84ciouL0Wg09Pb2qkFzaCaLXq8HwG63s2LFCl577TUURSExMZGOjg7sdjuR\nkZGUlZXR3d19Xd3nzJlDeXm5OnQjSXeLHFOX7hhFUdi9ezcpKSmkpKSwbt069WZpdHQ0q1evRqvV\nEh8fz+nTp4mIiCA+Pp7W1lYCgQAGg4HKysrrZpwMLeH/zGc+g9vtpqysjLKyMnp6eujo6ECn0+H3\n+2ltbeWjjz6ivLyc1atXc+bMGXVGS0REBPfeey9nz57F7/fT29uL1WqlpaUFk8mETqfDZrOpvX+X\ny8Xvfvc7MjIyWLBgAW63m/7+furq6rDZbMyYMUOt85w5c3jqqafQaDQyoEsTmgzq0m1766238Hg8\n3HvvvTQ2NqozW+Lj44mPj8dsNuN2uzEYDDQ1NREVFUUgEKClpYVAIEBXVxcul4v09HR27drF4sWL\nycjIICMjA6fTqb4uPDycrq4unE4nL7zwAvv372fXrl1qzzs7O5sTJ04QGhpKeHg4YWFhzJ8/n/7+\nfrxeL319fURFRbFy5UpWrlyJ3W7HaDRSVVVFWVkZ6enp9PT0MHPmTC5cuKBmc4TgsMtLL71EdHQ0\nGo38byNNXHL4RRoTeXl5pKWlUVNTQ1lZGUuWLKGjo4OKigo8Hg/h4eFYLBZ1/DoQCKDT6dTgOzQ0\nkpWVxb59+9Qc4i0tLSiKgtVqxWQy0dvbi16vR1EUNf9LeHi4unVeQkICly5dIjQ0lL6+Pj71qU9R\nXFysTrnU6XREREQAwZzmTqeTvr4+ent78fl8dHV1YTKZ2LRpE88++6xav9zcXKKjo9m3b9/dv7iS\nhBx+ke6yyMhIdVphYmIiHo+HsrIytWc9tOqzpaWF9vZ2wsPD1e3rOjo6KCgoIC0tjVdffRUIjnvr\n9Xo8Hg82mw2/38+jjz7KlStXuHr1Kr29vWzYsIGGhgY1BW9WVhZtbW18/etfJykpCb/fz5kzZ/D5\nfMTHx6sfHkOLpqKiouju7qazs5N58+bR3t5Oamoq+fn5PPvss2pumxdeeIGLFy9iMBjG8xJL0qjI\noC6NiQsXLmC1WtXc5c3NzbhcLu6//34yMzPV5F4Ac+fO5fLly6SkpFBZWUlzczN6vZ4//elP5Ofn\nq4uW/H4/sbGxDAwMYLFY2LJlC2lpaaxdu5ZAIEBPTw8ZGRmcP3+eL3/5ywwMDNDW1sbWrVvVDakV\nRWHp0qU0Njai0WhISEggLi5OTTGwe/duZs+eTXt7OzNmzODy5cusXr0ak8lEWVkZZrOZ3//+9+j1\nelwu1zhfZUm6OTn8Io2Zn//851RWVvKTn/yE7du3c/DgQbZv3w4Ek2f19PSg0WhwOBxYrVZCQkLU\nVaGRkZGUlpaSkZFBWVmZOk5uMplobW1l8eLFakrfuXPnUl9fT1dXF0IIUlJSqKmpITU1lRMnThAT\nE0N5eTkZGRm0trbS3t7Ol7/8ZV5//XUMBgMLFy4Egh9EHR0dzJ07l/Lycr7xjW+wdetWdDod58+f\nRwjBfffdh8fjYWBgQM02KUnjQQ6/SJIk/RWSPXXpjti8eTPHjx+ns7OTqKgoCgoKALBarTidTsrK\nytDpdOqNyqEbpW1tbTgcDtrb2wGIj4/n05/+NOfOnVM3k/7oo4+w2WzodDpqampITEzkc5/7HG+9\n9Rbx8fFYLBZOnTpFfn4+dXV1+P1+dWZMYmIivb29AAwMDKj7q3o8HrRaLffddx9r1qzh29/+Nt3d\n3TQ0NLB27VpCQ0M5cuTILW9dJ0m3S/bUpXE1Z84cZs2ape4QNDTkAahj5GlpaZSVlWG32+np6cHn\n85GQkIDFYlHzpqempvLqq69y5coVXC4Xx48fJzU1lf7+foQI/o7X19ezb98+kpOTKSsr4+LFiwgh\naGpqwuv1YrVayc3NZdasWXR0dNDd3U13dzd5eXl4vV4iIiJ49NFHCQ0NpauriyeffFJddLR+/Xoq\nKyuZNWuWDOjSpCB76tIdYTab+cIXvoDFYuH999+noqJCTcDV29tLb28vUVFRXL16lc2bN3Ps2DEi\nIyNpaGigrKyMN998E4Cf/vSn+Hw+vF4v5eXlJCYmqnPOhRA4nU510dOJEyfUtLoajYbGxkb8fj+L\nFi3i5MmTmM1m+vv71fnnzc3NrF69mkOHDlFfX8/9999PYmIir7zyCgDLly9n//79hISEYDQabzt/\nuiTdDtlTl8bVvHnzWLFiBe+88w6LFi3CaDSyZcsWBgYG1F2THA4H+fn5HD58mI6ODg4dOkRfXx8r\nV65k8+bNbN68mbq6OkpLS6msrGTdunXU1dWh0WgIBAIIIXjooYew2+0sWLBA3bO0ra2NgYEBhBBE\nRkZSUVFBe3s7Dz30EA6Hg6amJpqamoiNjWXnzp0YjUZSUlLweDxqPhsIzpkH1J8lSZOB7KlLYyY+\nPp7GxkYAVq9eTXR0NN3d3ezevZslS5aomRp1Oh1paWkkJyfz6quvEhUVhV6vJyUlhYKCAgKBALNm\nzQKgpqaG9vZ27HY7ISEhaibGoamKbrebgoICQkNDSUlJobe3Vw3YRqORmpoaAoEAFotFHfYZSk0A\nwc02hsbTp02bxoULF9TnZsyYwcWLF8nOzlbz1EjSeBltT11maZTGxNNPP43L5SIxMZHu7m7a2to4\nd+4cCxcuJC0tjb1797J06VKsVivHjh2jra2NRYsW4XQ68fv91NXVUV9fj6Io5OXlUVRUBEBERATh\n4eHU19eri5oiIiJobm6mr6+Pt6LBUQAAFHdJREFUsrIyALRaLYqioNVqCQ0N5erVq2i1WsLDwzGb\nzTQ1NZGfn09paam6b2lycjLFxcVotVpWrVql3swdMjTcMjyfuiRNZDKoS2OioKCApUuXsnv3bi5c\nuEBSUhIQTGWr0WjIy8sjEAhw9OhRwsLCiI6O5vnnn8dqtTJt2jSSk5MpLS3F6XSqq1AB2tvbycrK\nwmw209XVRX9/PyaTiezsbBoaGtBoNBiNRrRaLe3t7ZjNZpqbm9WsjgaDgc7OTubMmcO+ffvIz8/n\nzJkzQHAO/Lx588jJyeHcuXNUVVVdVyePx3Pdd0maDOSYujQm9u/fz86dO9myZQszZszA4XBQXl7O\n0aNHGRgYIDk5GZfLRXt7O6tXr+bAgQPk5uYSFRWFz+ejpKQEg8HAyy+/zMDAgLpJhtfrpaqqivz8\nfJqamvj0pz9NXl4eISEhtLS0EBISQkhICDabjZiYGCwWC7m5uZhMJpxOJy6XC4vFQmFhIWvXrsXr\n9WIymTCZTHR0dHDkyBHOnDlDT0/PX9RpKE3ARB+ilKRryaAujRm/38+PfvQjMjMzsVqtZGdn09fX\nh1ar5eDBg+Tn55OSksLRo0eJjY3F5/Nhs9m4fPkyeXl52O12vv3tb2O329HpdOh0OgwGA21tbRw9\nepTQ0FBOnTqF1+uls7OTGTNmkJubS3x8PFVVVfj9fqqrq9FoNGqgDwkJUWfZdHd3q7387OxsdWim\nuLgYRVH+Ysri0Fi73MBCmkxkUJdu2fr161m/fj1r1qwBoLi4GJPJRElJCY899hhOp5OMjAyuXLnC\nW2+9RXl5Ob29vWi1Wjo7O6mrq2PTpk189rOfpbKykqeffprTp09TW1uL3W7Hbrdz//33EwgECAkJ\nobOzk2eeeYaOjg4sFgtNTU189NFHGI1GdfPomTNnYjAY1G30Ojs7cTqd3H///epepVFRUURFRREd\nHY3D4SAuLu66m6dDGhoaSEhIkD11aVKRQV26ZUVFRRQVFXH27FmeeeYZNevhvffey9NPP01LSwsF\nBQXMnz+fjRs3cunSJTIzM7HZbOTn5+Pz+di5cycFBQXU1tby/PPPk5iYyEsvvURJSQklJSUUFBTg\ncDjUhGBvv/02V65cISEhgdDQUP7xH/8Rg8FAeno6R44cweFwcOHCBTo7O3n00UdZsWIF77//Poqi\nkJSURH19vZrQ68yZMwghmD59unrz9FoejweTyTQOV1aSbp28USrdstbWVgCeeuopjhw5wsyZMwkN\nDaW4uJhly5aRnJxMTk4O+/fvR6/Xs2zZMhoaGqioqFBXlPb29pKUlMTy5cvp6uri0KFDnDt3jry8\nPADcbjc2m43i4mK6u7uJjY3FYDBw6tQpNm3ahNfrZdOmTRQVFbFw4UJ1Q2ur1aqmA+7q6uK5557j\n+9//PhUVFcybNw+AL37xi4SHh1NYWPgXM1+GDM2ukaTJQvbUpVvm8XjweDzU1NSg1+sJBAIkJiaS\nmJiIoigcP36cnp4edQVnY2MjkZGRZGVl4XQ6+dKXvoQQgqNHj9La2srly5eJiIjg4MGDFBYWUlhY\nSEhICA8++CBpaWmYTCby8/MpKChg5cqVnDhxgosXL7Jw4UIaGhr49a9/TV1dHStXriQ1NZXXXnsN\ns9nM/Pnzueeee1i6dCmrV69m48aNbNy4kSNHjuByufjzn/88zldSksaOXHwk3Taj0cgjjzzCgw8+\nyL//+7+rNy4jIyNJTU2loKCA8+fPY7fbiYuLo7y8nLa2Nh555BFOnz6NxWIhJCSE8PBwNZd6c3Mz\nEFzNGRoaSkREBDU1NQgh6OvrY8OGDWpa3xux2+309vaSnZ1Nc3MzBoOBpKQkcnJyADh58iStra3U\n1tbe8WskSbdrtIuPZFCXbonBYFD36vT5fBw/fpxvfetbOJ1Oli9fjhCCLVu2IITAZrPxhS98gWef\nfRZFUQgEAkyfPp3y8nI1u+L8+fPJy8ujsrKSuLg49uzZAwRXdXZ2dtLQ0IDVamXdunX8x3/8B/n5\n+Zw+fZpAIPCJyp2amkpFRQUAS5cu5dChQ2N6XSTpTpFBXbrjoqOjAdQpf6+88gpms5kXX3yRAwcO\nkJOTQ29vL16vl4SEBGw2GyaTie7ubg4fPkx+fj45OTns2rWL7OxsPB4Pq1atYufOnTz44INAcFu7\nuLg4XnjhBdauXcuZM2fQ6XQsW7aMnp4efvCDH9xy+a1WK16v97avgyTdDTJNgHTHDZ+/vW/fPior\nKzEYDOzatYutW7dy5MgRlixZwuzZs9m2bRvx8fHU1dUxMDDAmjVreOONN4iLiyMkJIS6ujr++Mc/\n8sYbb/D2228DcPz4cWpqapg3bx47duygoaEBCI7nNzU1qYm2bqVzIgO6NBXJnro0ZtavX09iYiK1\ntbU0NjbS29ur5mHR6XTMnz+fwsJCTCYT4eHhuN1umpubcTgcdHR00NfXx7Rp09DpdPj9fgA+/PBD\nVq9eza5du8a5dpI0vmTqXemuyszM5I9//CO5ubnqnPLIyEji4+PJzs6mo6OD2tpa+vv7cTgc/PSn\nP1XnlVssFsLCwoiJiSE3N5ezZ8+iKAqKomA0GnnjjTfGu3qSNGnInro0pmbPns1jjz3GqVOnSE1N\nxeVyUVhYSHx8PIFAAL1eT2NjI2fPnmXBggUMDAzQ3NxMbm4u+/fvJzs7m6qqKmw2GwCLFi1i27Zt\n41spSZoA7tiNUiHEh8AiIFlRlDs+F0wG9cknJyeHTZs28fbbb9PV1YVGo+HUqVOkpKSQmpqK2Wwm\nKiqKmTNncvjwYTo7Ozl37hxmsxmv18uvfvUrnnnmGQDCwsI4fvz4ONdIksbfHQnqQogHgTcABUi5\nNqgLIazAc8AKIADUA/+sKMrFYe+hB74HPAT0A53AtxRFOXqDnymD+iTjdDqZOXMmK1asICoqih07\ndqhj7IsXL8btduPz+TAYDJSVlZGQkIDRaKS8vBwhBFqtlsTERCA4l7yzs3OcayRJ42/Mg7oQwgBc\nAMqANQzrqQshdgMWYKWiKD4hxBbga8BsRVEarznvl8BSYJGiKG1CiE3AfwELFUU5P8LPlUF9krFa\nrWzfvp3f/OY3dHd3k5SURGtrK2FhYUBw04menh5178+amhrq6+vJzs6moqICh8PB1atXAbh06dJ4\nVkWSJow7caP0fwMngFPDnxBCfAZYBXxPURTf4OEfAlrgO9eclwk8ATynKErbYEFfAqqAZz9BWSRJ\nkqQRjCqoCyEigG8C/xcY6dPiQaAPODJ0QFEUP3B08LkhfzP4+oPDXn8QWCmEMI+65NKE5fV6efjh\nh7HZbOTl5fHKK69QUVHBk08+yTvvvEN1dTVNTU2cOHGCvr4+MjIySEtLw+1209bWRnR0NOnp6aSn\np493VSRp0hltT/17wKuKotTd4PlcoFFRlOGbOVYDMUKIyGvOCwDDb7BWEVwINWOU5ZEmuKHNo2fO\nnMmyZcuIjo6mpqaGFStWUFJSQnl5OV6vl0AgQFVVFU6nE51OR0ZGBh988IGa8/x3v/vdeFdFkiaV\nmwZ1IUQ68Hk+fngkEhhpI8ehO1yOa87rVv5yIH/4edIU0N/fz1tvvcXTTz9NcnIyzz33HGfPnuXy\n5ctMmzaNxx9/nH/913/FarVSV1eH3++nt7eXuXPn4vV68Xq9PP/88yNuYCFJ0shG01N/Hvg3RVHk\n7rvSqLz44osoisJ3vvMd7HY77733HqWlpaxatYrW1lY2btzIQw89xN69e1mzZg1XrlxBr9djNpuZ\nO3cuFouFPXv2sGfPHlJSUliwYMF4V0mSJo2PDepCiCVADvDLkZ6+5t9uIHSEc2yD39uuOc8ihhJ2\n3Pg8aRJrbW3lnnvuoba2lhMnTvCLX/wCq9XK//zP/xAIBLBYLLz66quUlpbi9/tpamqiqqqKrVu3\ncvnyZTQaDU888QRPPPEEFRUVLF68mKysrPGuliRNCh87pVEI8QzwGNcPrcQCMUAJwZuj3wHWAV8B\nLNeOqwsh3gXyFUWJH3z8beDf+MvpkC8AXwXCFUXpHlYGOaVxklmxYgV5eXm43W4aGxt55ZVXSElJ\nISsri3vuuYfCwkIcDgeJiYn8/ve/Jz8/n8LCQrKzs4FgKl+zOXjPPCUlBa1Wy69//evxrJIkjbs7\nuaL0+8D3uSYwD05pfB9YpijKB4PHDEAz8FtFUZ4cPJZB8MPgK4qibL/mPYuBKkVRPjfCz5NBfRI6\ndOgQW7ZsYc6cOfT391NcXExnZyeXL19m+/btNDY2smPHDnXTjJycHPR6PZWVlWg0GiwWCxAclz95\n8qQ6b12S/lrdyaD+A4KzYVIURam55vjQ4qNViqL0DPbyhxYfNV1z3i+AZfz/xUcbga3AAkVRCkf4\neTKoTyIPPfQQtbW1zJs3j6amJkpLS4mPjweC+dd7enpQFAWLxYLb7aa8vJzvfve7PP7442zYsIHI\nyEiMRiMulwsIptgd2jBDkv6a3YkVpRuAnwF2gmPgjYBfUZTpg89bCN5U/QzBaYt1wD8pilIy7H10\nBHv6nwf8yDQBU4YQ4rq85l/84hdZv349L730EsnJyZhMJvr6+nj33XfJyMjgwIEDI77Pww8/TF1d\ncPaszPsiSUFy5yNpwggPD+eee+5BURQ+/PBDfD7fzV8kSdJ1ZFCXJEmaQuQmGZIkSX+FZFCXJEma\nQmRQlyRJmkJkUJckSZpCZFCXJEmaQmRQlyRJmkJkUJckSZpCZFCXJEmaQmRQlyRJmkJkUJckSZpC\nZFCXJEmaQmRQlyRJmkJkUJckSZpCZFCXJEmaQmRQlyRJmkJkUJckSZpCZFCXJEmaQmRQlyRJmkJk\nUJckSZpCZFCXJEmaQmRQlyRJmkJkUJckSZpCZFCXJEmaQmRQlyRJmkKEoijjXQZJkiRpjMieuiRJ\n0hQig7okSdIUIoO6JEnSFCKDunQdIUScEGKPEGJgvMsyFqZafSTpZiZsUBdCRAshfiuEKB38ekMI\nkTDe5boZIUSyEMIrhDg7wlfYNedZhRBbB+t2QQjxvhBixjiX/W+Bo0AycMM76KMtuxBCL4T4oRCi\nRAhRJIQ4KoRYdOdq8Bc/f7T16btBe2UNO2+86zNbCPFrIcRFIUTh4LX/TyFE5LDzJkv7jLY+k6V9\nUoUQPxFCnB78KhNCHBZCrBl23p1tH0VRJtwXYADOA38g+MGjAbYBlwDLeJfvJmVPBg6O4rzdwGHA\nOPh4C9ACxI9j2YcC4DZg4HbLDvwSKAUcg483AV3ArAlWn6pRvt9416cUeAMwDT6OB0qAsqG2mGTt\nM9r6TJb2+TpQB0wffCyAHwH9wH13q33ueEVv8eI8AQwAydccixm8ON8c7/LdpOzJ3CSoA58ZrN/S\na47pgTZg6ziWfWiK6w2D4GjLDmQCAeDxYa8vBt6bKPUZfL5qFO81EepzcShgXHPsK4Pt8beTsH1u\nWp9J1j4bgK8MOxY2WJ+f3K32majDLw8CNYqiVA8dUBTFRfCX4MHxKtQYehDoA44MHVAUxU+wZzlu\n9VMGf2tuYrRl/xuCPZWDw15/EFgphDDfXmlvbpT1Ga1xrw+QqyhK5bBjTYPf7YPfJ037MLr6jNa4\n10dRlHcURfnvYYeHhlxbB7/f8faZqEE9F6ga4Xg18Km7W5RbEiOEeFUIcWJwXO23QoiZ1zyfCzQq\nitI/7HXVg6+NZOIabdlzCfY0aoedVwXogHG9fzCMWQjxohDimBDikhDiHSHE4mHnjHt9RrjmABkE\n7xccHnw8adpnlPWBSdI+ww3eA/w5cGbwO9yF9pmoQT0S8IxwvJNgA4fc5fJ8EgGCw0Q/VRTlXmAu\n4AdOCCHmDp7zcfUDcNzxUt660ZY9Eugeobc8EevYBbypKMpCgv+ZLgKHhBDrrjlnwtVHCKElOM76\nG0VRLg8enrTtc4P6wCRrn8EbppcJjq8L4G8URfEOPn3H22eiBvVJm7tAUZQ6RVFyFUU5O/jYA3yN\n4C/mj8a1cNKIFEWZrijKgcF/+xRF+Q7BG3Y/Gd+S3dR3gV7gn8a7IGNkxPpMtvZRFKVCUZQ0gkMv\n5cD5uzkLZ6IGdTcQOsJxG9ClKErvXS7PbVEUxUfwBse9g4c+rn4QvGkyUY227G7AIoQQNzlvojoF\npAkhwgcfT6j6CCE2Ag8BqxVF6bnmqUnZPh9TnxuZ0O0DwQ6doij/DLiAFwcP3/H2mahBvRBIGeF4\nClB0l8vyiQghbEII/QhPBQDt4L8LgQQhhG7YOSlAs6Io7jtZxts02rKfJ/j7NW2E8/wE/4Qed0II\nixDCOMJTgcHv17bZhKiPEOJ/Ad8A7h/hd2XStc/H1Wcytc8NygnBDl2OEMLAXWifiRrUdwJOIYRz\n6IAQIgbIAt4at1KNzn8xbAbLYGN+CigYPPQWwWlMi4ads4iJU78bDYGNtuxvD77HsmGvXwbsVRSl\ne+yKOio3qs/TjDx8kQ/UX/OfbCcToD5CiL8DvgUsVxSlZfDYWiHEE4OnTKr2GUV9JlP77BFCzB/h\neDLQqShKH8Fy3tn2uRvzN29hvqee4CfV7wl+EmuAlwkuSjCPd/luUvaXCd7tjh18rAX+k+Cn6/Jr\nzhtagDC08OIZgn+mxU2AOmxjdIuPPrbswC+4fvHERoL3FnInSn2A7wM1QOo1x75JcC7x4xOpPsBj\nQA/wf4C/u+brV8D3J1v7jKY+k6x9DgLvAxGDjwXw1GBZf3C32ueu/ce6hQsUDfyWYCAfWnmWMN7l\nGkW5ZwIvAOcGv+qBvcCnh51nAbYO1u/i4C9D9jiX/UWCU6Y8BP+8rQIqAf2tlJ3g1KsfDrZfEcG5\nuIsmUn0I9qKeI/hX1FmCU8iOEJyxMNHq0zZYj4FhXwHge5OwfW5an0nWPguB/x782WcJ3sz9EHj0\nbv7/kZtkSJIkTSETdUxdkiRJugUyqEuSJE0hMqhLkiRNITKoS5IkTSEyqEuSJE0hMqhLkiRNITKo\nS5IkTSEyqEuSJE0hMqhLkiRNIf8PNxnoqwMVBRAAAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x10cb01e90>"
       ]
      }
     ],
     "prompt_number": 15
    },
    {
     "cell_type": "heading",
     "level": 6,
     "metadata": {},
     "source": [
      "Population density in the Nordic countries (Denmark is missing)"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Our $S$ matrix, the susceptible individuals should be something like the population density. The infected $I$ is for now just zeros. But let's put a patient zero somewhere in Stockholm."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "S_0 = img[:,:,1]\n",
      "I_0 = np.zeros_like(S_0)\n",
      "I_0[309,170] = 1 # patient zero"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 8
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Nobodys dead, yet. So lets put $R$ to zeroes too."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "R_0 = np.zeros_like(S_0)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 9
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Now set some initial values of how long the simulation is to be run and so on."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "T = 900                         # final time\n",
      "dt = 1                          # time increment\n",
      "N = int(T/dt) + 1               # number of time-steps\n",
      "t = np.linspace(0.0, T, N)      # time discretization\n",
      "\n",
      "# initialize the array containing the solution for each time-step\n",
      "u = np.empty((N, 3, S_0.shape[0], S_0.shape[1]))\n",
      "u[0][0] = S_0\n",
      "u[0][1] = I_0\n",
      "u[0][2] = R_0"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 10
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "We need to make a custom colormap so that the infected matrix can be overlayed on the map."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import matplotlib.cm as cm\n",
      "theCM = cm.get_cmap(\"Reds\")\n",
      "theCM._init()\n",
      "alphas = np.abs(np.linspace(0, 1, theCM.N))\n",
      "theCM._lut[:-3,-1] = alphas"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 11
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "And we sit back and enjoy..."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "for n in range(N-1):\n",
      "    u[n+1] = euler_step(u[n], f, dt)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 12
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Not let's render some images and make a gif of it. Everybody loves gifs!"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from images2gif import writeGif\n",
      "\n",
      "keyFrames = []\n",
      "frames = 60.0\n",
      "\n",
      "for i in range(0, N-1, int(N/frames)):\n",
      "    imgplot = plt.imshow(img, vmin=0, vmax=255)\n",
      "    imgplot.set_interpolation(\"nearest\")\n",
      "    imgplot = plt.imshow(u[i][1], vmin=0, cmap=theCM)\n",
      "    imgplot.set_interpolation(\"nearest\")\n",
      "    filename = \"outbreak\" + str(i) + \".png\"\n",
      "    plt.savefig(filename)\n",
      "    keyFrames.append(filename)\n",
      "  \n",
      "images = [Image.open(fn) for fn in keyFrames]\n",
      "gifFilename = \"outbreak.gif\"\n",
      "writeGif(gifFilename, images, duration=0.3)\n",
      "plt.clf()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "60 frames written\n"
       ]
      }
     ],
     "prompt_number": 13
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "![alt text](outbreak.gif \"Title\")"
     ]
    },
    {
     "cell_type": "heading",
     "level": 6,
     "metadata": {},
     "source": [
      "The spread of infection as a gif. Even the Finns will succumb."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Look at that! The only safe place seem to be in the northern parts where it's not so densly populated. Even Finland will at the end of the animation be infected. Now you know.\n",
      "\n",
      "If you want to know more about solving differential equations I can warmly recommend [Practical Numerical Methods with Python](http://openedx.seas.gwu.edu/courses/GW/MAE6286/2014_fall/about) by [@LorenaABarba](https://twitter.com/LorenaABarba). Here you'll learn all the real numerical methods that should be used instead of the simple one in this post.\n",
      "\n",
      "**UPDATE**: To play around for yourself, the Ipython notebook can be found [here](https://github.com/maxberggren/blog-notebooks/blob/master/SweEbola.ipynb)."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 13
    }
   ],
   "metadata": {}
  }
 ]
}